def publish_rx_spectrum(self,fftlen):
## RX Spectrum
fftlen = 256
my_window = window.hamming(fftlen) #.blackmanharris(fftlen)
rxs_sampler = vector_sampler(gr.sizeof_gr_complex,fftlen)
rxs_trigger = gr.vector_source_b(concatenate([[1],[0]*199]),True)
rxs_window = blocks.multiply_const_vcc(my_window)
rxs_spectrum = gr.fft_vcc(fftlen,True,[],True)
rxs_mag = gr.complex_to_mag(fftlen)
rxs_avg = gr.single_pole_iir_filter_ff(0.01,fftlen)
rxs_logdb = gr.nlog10_ff(20.0,fftlen,-20*log10(fftlen))
rxs_decimate_rate = gr.keep_one_in_n(gr.sizeof_float*fftlen,1)
msgq = gr.msg_queue(5)
rxs_msg_sink = gr.message_sink(gr.sizeof_float*fftlen,msgq,True)
self.connect(rxs_trigger,(rxs_sampler,1))
t = self.u if self.filter is None else self.filter
self.connect(t,rxs_sampler,rxs_window,
rxs_spectrum,rxs_mag,rxs_avg,rxs_logdb, rxs_decimate_rate,
rxs_msg_sink)
self.servants.append(corba_data_buffer_servant("spectrum",fftlen,msgq))
print "RXS trigger unique id", rxs_trigger.unique_id()
print "Publishing RX baseband under id: spectrum"
def build_blocks( self, vlen, cp_len, snr_db, sigpow, startup, N,
LOS_power, no_taps, have_LOS ):
self.fading_channel = \
static_fading_channel( LOS_power, no_taps, vlen, have_LOS )
self.freq_resp = self.fading_channel.freq_resp
assert( len(self.freq_resp) == vlen )
############################################################################
# select channel estimator to be tested her
# self.uut = channel_estimator_003( vlen, cp_len )
self.uut = channel_estimator_001( vlen)
############################################################################
block = self.uut.preamble_td
#print abs(sigpow)
#print sum(numpy.abs(block)**2.0)/len(block)
assert( abs( sigpow - sum(numpy.abs(block)**2.0)/len(block) ) < 1e-4 ) # power
if cp_len > 0:
block = concatenate([ block[ len(block) - cp_len : len(block) ], block ])
self.block = block
self.compare = gr.add_const_vcc( -1.0 * numpy.array(self.freq_resp) )
self.mean_squared_error = vector_acc_se2( vlen, startup, N )
self.dst = gr.vector_sink_f()
self.awgn_channel = awgn_channel( snr_db, sigpow )
self.block_src = gr.vector_source_c( self.block, True )
self.sampler = ofdm.vector_sampler( gr.sizeof_gr_complex, vlen )
self.perfect_trigger = perfect_block_trigger( len(self.block) )
self.fft = scaled_fft( vlen )
def supply_rx_baseband(self):
## RX Spectrum
if self.__dict__.has_key('rx_baseband'):
return self.rx_baseband
config = self.config
fftlen = config.fft_length
my_window = window.hamming(fftlen) #.blackmanharris(fftlen)
rxs_sampler = vector_sampler(gr.sizeof_gr_complex, fftlen)
rxs_trigger = blocks.vector_source_b(concatenate([[1], [0] * 199]),
True)
rxs_window = blocks.multiply_const_vcc(my_window)
rxs_spectrum = gr.fft_vcc(fftlen, True, [], True)
rxs_mag = gr.complex_to_mag(fftlen)
rxs_avg = gr.single_pole_iir_filter_ff(0.01, fftlen)
rxs_logdb = gr.nlog10_ff(20.0, fftlen, -20 * log10(fftlen))
rxs_decimate_rate = gr.keep_one_in_n(gr.sizeof_float * fftlen, 50)
t = self.u if self.filter is None else self.filter
self.connect(rxs_trigger, (rxs_sampler, 1))
self.connect(t, rxs_sampler, rxs_window, rxs_spectrum, rxs_mag,
rxs_avg, rxs_logdb, rxs_decimate_rate)
if self._options.log:
log_to_file(self, rxs_decimate_rate, "data/supply_rx.float")
self.rx_baseband = rxs_decimate_rate
return rxs_decimate_rate
def main():
parser = OptionParser(conflict_handler="resolve")
expert_grp = parser.add_option_group("Expert")
add_options(parser, expert_grp)
(options, args) = parser.parse_args()
fft_length = options.fft_length or 512
file = options.file or "input.compl"
out = options.out or "output.compl"
src = gr.file_source(gr.sizeof_gr_complex, file)
sampler = ofdm.vector_sampler(gr.sizeof_gr_complex, fft_length)
trig = gr.vector_source_b([1], True)
fft = gr.fft_vcc(fft_length, True, [], True)
mag = gr.complex_to_mag(fft_length)
avg = gr.single_pole_iir_filter_ff(0.01, fft_length)
nlog = gr.nlog10_ff(20, fft_length, -10 * math.log10(fft_length))
dst = gr.file_sink(gr.sizeof_float * fft_length, out)
fg = gr.top_block()
fg.connect(src, sampler, fft, mag, avg, nlog, dst)
fg.connect(trig, (sampler, 1))
# fg.connect(src,limit,
# gr.stream_to_vector(gr.sizeof_gr_complex,fft_length),
# fft,
# gr.multiply_const_vcc([1./fft_length]*fft_length),
# gr.complex_to_mag(fft_length),
# gr.nlog10_ff(10.0,fft_length),
# dst)
# fg.connect( src, fft, dst )
fg.run()
print "done"
def main():
parser = OptionParser(conflict_handler="resolve")
expert_grp = parser.add_option_group("Expert")
add_options(parser, expert_grp)
(options, args) = parser.parse_args ()
fft_length = options.fft_length or 512
file = options.file or "input.compl"
out = options.out or "output.compl"
src = gr.file_source(gr.sizeof_gr_complex,file)
sampler = ofdm.vector_sampler( gr.sizeof_gr_complex, fft_length )
trig = gr.vector_source_b([1],True)
fft = gr.fft_vcc( fft_length, True, [], True )
mag = gr.complex_to_mag( fft_length )
avg = gr.single_pole_iir_filter_ff(0.01, fft_length)
nlog = gr.nlog10_ff( 20, fft_length, -10*math.log10(fft_length) )
dst = gr.file_sink( gr.sizeof_float * fft_length, out )
fg = gr.top_block()
fg.connect( src, sampler, fft, mag, avg, nlog, dst )
fg.connect( trig, (sampler,1))
# fg.connect(src,limit,
# gr.stream_to_vector(gr.sizeof_gr_complex,fft_length),
# fft,
# gr.multiply_const_vcc([1./fft_length]*fft_length),
# gr.complex_to_mag(fft_length),
# gr.nlog10_ff(10.0,fft_length),
# dst)
# fg.connect( src, fft, dst )
fg.run()
print "done"
def __init__(self,subcarriers, frame_length):
#config = station_configuration()
total_subc = subcarriers
vlen = total_subc
gr.hier_block2.__init__(self,"ofdm_frame_sampler_grc",
gr.io_signature2(2,2,gr.sizeof_gr_complex*vlen,
gr.sizeof_char),
gr.io_signature2(2,2,gr.sizeof_gr_complex*vlen,
gr.sizeof_char))
ft = [0] * frame_length
ft[0] = 1
# The next block ensures that only complete frames find their way into
# the old outer receiver. The dynamic frame start trigger is hence
# replaced with a static one, fixed to the frame length.
frame_sampler = vector_sampler( gr.sizeof_gr_complex * total_subc,
frame_length )
symbol_output = blocks.vector_to_stream( gr.sizeof_gr_complex * total_subc,
frame_length )
delayed_frame_start = blocks.delay( gr.sizeof_char, frame_length - 1 )
damn_static_frame_trigger = blocks.vector_source_b( ft, True )
self.connect( self, frame_sampler, symbol_output, self )
self.connect( (self,1), delayed_frame_start, ( frame_sampler, 1 ) )
self.connect( damn_static_frame_trigger, (self,1) )
def __init__(self, vlen):
gr.hier_block2.__init__(self, "coarse_frequency_offset_estimation",
gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
gr.io_signature (1,1,gr.sizeof_float))
## Preamble Extraction
sampler = vector_sampler(gr.sizeof_gr_complex,vlen)
self.connect(self,sampler)
self.connect((self,1),(sampler,1))
## Split block into two parts
splitter = gr.vector_to_streams(gr.sizeof_gr_complex*vlen/2,2)
self.connect(sampler,splitter)
## Multiply 2nd sub-part with conjugate of 1st sub-part
conj_mult = gr.multiply_conjugate_cc(vlen/2)
self.connect((splitter,1),(conj_mult,0))
self.connect((splitter,0),(conj_mult,1))
## Sum of Products
psum = vector_sum_vcc(vlen/2)
self.connect((conj_mult,0),psum)
## Complex to Angle
angle = complex_to_arg()
self.connect(psum,angle)
## Normalize
norm = gr.multiply_const_ff(1.0/math.pi)
self.connect(angle,norm)
## Setup Output Connections
self.connect(norm,self)
def __init__(self, fft_length):
gr.hier_block2.__init__(
self, "foe",
gr.io_signature2(2, 2, gr.sizeof_gr_complex, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_float))
self.input = (self, 0)
self.time_sync = (self, 1)
# P(d)
self.nominator = schmidl_nominator(fft_length)
# sample nominator
sampler = vector_sampler(gr.sizeof_gr_complex, 1)
self.connect(self.input, self.nominator, (sampler, 0))
self.connect(self.time_sync, (sampler, 1))
# calculate epsilon from P(d), epsilon is normalized fractional frequency offset
angle = complex_to_arg()
self.epsilon = gr.multiply_const_ff(1.0 / math.pi)
self.connect(sampler, angle, self.epsilon, self)
try:
gr.hier_block.update_var_names(self, "foe", vars())
gr.hier_block.update_var_names(self, "foe", vars(self))
except:
pass
def __init__(self, fft_length):
gr.hier_block2.__init__(self, "foe",
gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
gr.io_signature(1,1,gr.sizeof_float))
self.input = (self,0)
self.time_sync = (self,1)
# P(d)
self.nominator = schmidl_nominator(fft_length)
# sample nominator
sampler = vector_sampler(gr.sizeof_gr_complex,1)
self.connect(self.input, self.nominator, (sampler,0))
self.connect(self.time_sync, (sampler,1))
# calculate epsilon from P(d), epsilon is normalized fractional frequency offset
angle = complex_to_arg()
self.epsilon = gr.multiply_const_ff(1.0/math.pi)
self.connect(sampler, angle, self.epsilon, self)
try:
gr.hier_block.update_var_names(self, "foe", vars())
gr.hier_block.update_var_names(self, "foe", vars(self))
except:
pass
def __init__(self, vlen):
gr.hier_block2.__init__(
self, "coarse_frequency_offset_estimation",
gr.io_signature2(2, 2, gr.sizeof_gr_complex, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_float))
## Preamble Extraction
sampler = vector_sampler(gr.sizeof_gr_complex, vlen)
self.connect(self, sampler)
self.connect((self, 1), (sampler, 1))
## Split block into two parts
splitter = gr.vector_to_streams(gr.sizeof_gr_complex * vlen / 2, 2)
self.connect(sampler, splitter)
## Multiply 2nd sub-part with conjugate of 1st sub-part
conj_mult = gr.multiply_conjugate_cc(vlen / 2)
self.connect((splitter, 1), (conj_mult, 0))
self.connect((splitter, 0), (conj_mult, 1))
## Sum of Products
psum = vector_sum_vcc(vlen / 2)
self.connect((conj_mult, 0), psum)
## Complex to Angle
angle = complex_to_arg()
self.connect(psum, angle)
## Normalize
norm = gr.multiply_const_ff(1.0 / math.pi)
self.connect(angle, norm)
## Setup Output Connections
self.connect(norm, self)
def supply_rx_baseband(self):
## RX Spectrum
if self.__dict__.has_key('rx_baseband'):
return self.rx_baseband
config = self.config
fftlen = config.fft_length
my_window = window.hamming(fftlen) #.blackmanharris(fftlen)
rxs_sampler = vector_sampler(gr.sizeof_gr_complex,fftlen)
rxs_trigger = gr.vector_source_b(concatenate([[1],[0]*199]),True)
rxs_window = blocks.multiply_const_vcc(my_window)
rxs_spectrum = gr.fft_vcc(fftlen,True,[],True)
rxs_mag = gr.complex_to_mag(fftlen)
rxs_avg = gr.single_pole_iir_filter_ff(0.01,fftlen)
rxs_logdb = gr.nlog10_ff(20.0,fftlen,-20*log10(fftlen))
rxs_decimate_rate = gr.keep_one_in_n(gr.sizeof_float*fftlen,50)
t = self.u if self.filter is None else self.filter
self.connect(rxs_trigger,(rxs_sampler,1))
self.connect(t,rxs_sampler,rxs_window,
rxs_spectrum,rxs_mag,rxs_avg,rxs_logdb, rxs_decimate_rate)
if self._options.log:
log_to_file(self, rxs_decimate_rate, "data/supply_rx.float")
self.rx_baseband = rxs_decimate_rate
return rxs_decimate_rate
def test_007_vector_sampler(self):
data = range(1,577,1) # 1..576
trigger = numpy.concatenate([[0]*575,[1]])
blocks = 10000
expected = data[64:577]
assert(len(expected)==512)
expected = numpy.concatenate([expected*blocks])
assert(len(expected) == 512*blocks)
src = gr.vector_source_c(data,True)
src2 = gr.vector_source_b(trigger.tolist(),True)
dst = gr.vector_sink_c()
sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,512)
v2s = gr.vector_to_stream(gr.sizeof_gr_complex,512)
self.fg.connect(src, (sampler,0))
self.fg.connect(src2,gr.head(gr.sizeof_char,blocks*576), (sampler,1))
self.fg.connect(sampler, v2s, dst)
self.fg.run()
#self.assertEqual(numpy.array(expected,numpy.Complex), numpy.array(dst.data(), numpy.Complex))
if numpy.array(expected).all() != numpy.array(dst.data()).all():
print "up"
print len(expected),len(dst.data())
vec = dst.data()
for i in range(min(len(expected),len(dst.data()))):
if vec[i] != expected[i]:
print "e at ",i
def __init__( self, vlen, cp_len ):
gr.hier_block2.__init__( self,
"perfect_ofdm_block_sampler",
gr.io_signature( 1, 1, gr.sizeof_gr_complex ),
gr.io_signature( 1, 1, gr.sizeof_gr_complex * vlen ) )
sampler = ofdm.vector_sampler( gr.sizeof_gr_complex, vlen )
perfect_trigger = perfect_block_trigger( vlen + cp_len )
self.connect( self, sampler, self )
self.connect( perfect_trigger, ( sampler, 1 ) )
self.perfect_trigger = perfect_trigger
def __init__(self,options):
config = station_configuration()
total_subc = config.subcarriers
vlen = total_subc
gr.hier_block2.__init__(self,"ofdm_frame_sampler",
gr.io_signature2(2,2,gr.sizeof_gr_complex*vlen,
gr.sizeof_char),
gr.io_signature2(2,2,gr.sizeof_gr_complex*vlen,
gr.sizeof_char))
ft = [0] * config.frame_length
ft[0] = 1
# The next block ensures that only complete frames find their way into
# the old outer receiver. The dynamic frame start trigger is hence
# replaced with a static one, fixed to the frame length.
frame_sampler = ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc,
config.frame_length )
symbol_output = blocks.vector_to_stream( gr.sizeof_gr_complex * total_subc,
config.frame_length )
delayed_frame_start = blocks.delay( gr.sizeof_char, config.frame_length - 1 )
damn_static_frame_trigger = blocks.vector_source_b( ft, True )
#oqam_postpro = ofdm.fbmc_oqam_postprocessing_vcvc(total_subc,0,0)
if options.enable_erasure_decision:
self.frame_gate = vector_sampler(
gr.sizeof_gr_complex * total_subc * config.frame_length, 1 )
self.connect( self, frame_sampler, self.frame_gate,
symbol_output )
else:
self.connect( self, frame_sampler, symbol_output, self )
self.connect( (self,1), delayed_frame_start, ( frame_sampler, 1 ) )
self.connect( damn_static_frame_trigger, (self,1) )
def publish_tm_window(self,unique_id):
"""
corbaname: ofdm_ti.unique_id
"""
raise SystemError,"Bad guy! Obey the gnuradio hierarchy ..."
config = self.config
msgq = gr.msg_queue(10)
msg_sink = gr.message_sink(gr.sizeof_float*config.fft_length,msgq,True)
sampler = vector_sampler(gr.sizeof_float,config.fft_length)
self.connect(self.receiver.timing_metric,(sampler,0))
self.connect(self.receiver.time_sync,delay(gr.sizeof_char,config.fft_length/2-1),(sampler,1))
self.connect(sampler,msg_sink)
self.servants.append(corba_data_buffer_servant(str(unique_id),config.fft_length,msgq))
def __init__(self, total_subcarriers, frame_length, frame_data_part,
training_data):
#config = station_configuration()
total_subc = total_subcarriers
vlen = total_subc
gr.hier_block2.__init__(
self, "fbmc_frame_sampler_grc",
gr.io_signature2(2, 2, gr.sizeof_gr_complex * vlen,
gr.sizeof_char),
gr.io_signature2(2, 2, gr.sizeof_gr_complex * vlen,
gr.sizeof_char))
frame_size = frame_data_part + training_data.fbmc_no_preambles / 2
print "frame_size: ", frame_size
ft = [0] * frame_size
ft[0] = 1
# The next block ensures that only complete frames find their way into
# the old outer receiver. The dynamic frame start trigger is hence
# replaced with a static one, fixed to the frame length.
frame_sampler = vector_sampler(gr.sizeof_gr_complex * total_subc,
frame_size)
symbol_output = blocks.vector_to_stream(
gr.sizeof_gr_complex * total_subc, frame_size)
#delayed_frame_start = blocks.delay( gr.sizeof_char, config.frame_length-1 - config.training_data.fbmc_no_preambles/2 )
delayed_frame_start = blocks.delay(gr.sizeof_char,
frame_length / 2 - 1)
damn_static_frame_trigger = blocks.vector_source_b(ft, True)
#oqam_postpro = ofdm.fbmc_oqam_postprocessing_vcvc(total_subc,0,0)
self.connect(self, frame_sampler, symbol_output, self)
#self.connect( (self,1), blocks.keep_m_in_n(gr.sizeof_char,frame_data_part + training_data.fbmc_no_preambles/2,2*frame_data_part + training_data.fbmc_no_preambles,0),delayed_frame_start, ( frame_sampler, 1 ) )
self.connect((self, 1), delayed_frame_start, (frame_sampler, 1))
#self.connect( self, blocks.multiply_const_vcc(([1.0]*total_subc)) ,self)
#terminate_stream(self,frame_sampler)
self.connect(damn_static_frame_trigger, (self, 1))
def test_008(self):
vlen = 128
syms = 4
bin1 = vlen / 2 + 4
bin1_val = 1.0
cp_length = vlen / 4
expec = numpy.array(numpy.zeros(vlen), numpy.complex)
expec[bin1] = bin1_val
expec = concatenate([expec] * syms)
epsilon = [-0.5]
frame_trigger = numpy.concatenate([[1], [0] * (syms - 1)])
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0 / vlen, cp_length)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
fft_scale = gr.multiply_const_vcc([1.0 / vlen] * vlen)
sampler = ofdm.vector_sampler(gr.sizeof_gr_complex, vlen)
trigger_vec = concatenate([[0] * (vlen + cp_length - 1), [1]])
trigger_vec = concatenate([trigger_vec] * syms)
trigger = gr.vector_source_b(trigger_vec.tolist())
src = gr.sig_source_c(vlen, gr.GR_COS_WAVE, 4.5, 1.0,
0.0) # bin vlen/2 + 4.5
dst = gr.vector_sink_c()
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f(epsilon)
trig = gr.vector_source_b(frame_trigger.tolist())
self.fg.connect(src, (sampler, 0))
self.fg.connect(trigger, (sampler, 1))
self.fg.connect(sampler, (freq_shift, 0))
self.fg.connect(eps, (freq_shift, 1))
self.fg.connect(trig, (freq_shift, 2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual2(expec, dst.data(), 1e-5, 1e-5)
def __init__(self, fft_length, L):
gr.hier_block2.__init__(self, "morelli_foe",
gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
gr.io_signature(1,1,gr.sizeof_float))
data_in = (self,0)
trig_in = (self,1)
est_out = (self,0)
#inp = gr.kludge_copy(gr.sizeof_gr_complex)
#self.connect(data_in,inp)
inp = data_in
sampler = vector_sampler(gr.sizeof_gr_complex,fft_length)
self.connect(inp,(sampler,0))
self.connect(trig_in,(sampler,1))
est = mm_frequency_estimator(fft_length,L)
self.connect(sampler,est,est_out)
def test_008 (self):
vlen = 128
syms = 4
bin1 = vlen/2 + 4
bin1_val = 1.0
cp_length = vlen/4
expec = numpy.array(numpy.zeros(vlen), numpy.complex)
expec[bin1] = bin1_val
expec = concatenate([expec]*syms)
epsilon = [-0.5]
frame_trigger = numpy.concatenate([[1],[0]*(syms-1)])
freq_shift = ofdm.frequency_shift_vcc(vlen, 1.0/vlen, cp_length)
fft = gr.fft_vcc(vlen, True, [], True) # natural order, dc = vlen / 2
fft_scale = gr.multiply_const_vcc([1.0/vlen]*vlen)
sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,vlen)
trigger_vec = concatenate([[0]*(vlen+cp_length-1),[1]])
trigger_vec = concatenate([trigger_vec]*syms)
trigger = gr.vector_source_b(trigger_vec.tolist())
src = gr.sig_source_c(vlen, gr.GR_COS_WAVE, 4.5, 1.0, 0.0) # bin vlen/2 + 4.5
dst = gr.vector_sink_c()
v2s = gr.vector_to_stream(gr.sizeof_gr_complex, vlen)
eps = gr.vector_source_f(epsilon)
trig = gr.vector_source_b(frame_trigger.tolist())
self.fg.connect(src, (sampler,0))
self.fg.connect(trigger, (sampler,1))
self.fg.connect(sampler, (freq_shift,0))
self.fg.connect(eps, (freq_shift,1))
self.fg.connect(trig, (freq_shift,2))
self.fg.connect(freq_shift, fft, fft_scale, v2s, dst)
self.fg.run()
self.assertComplexTuplesAlmostEqual2(expec, dst.data(), 1e-5, 1e-5)
def __init__(self,options):
config = station_configuration()
total_subc = config.subcarriers
vlen = total_subc
gr.hier_block2.__init__(self,"fbmc_frame_sampler",
gr.io_signature2(2,2,gr.sizeof_gr_complex*vlen,
gr.sizeof_char),
gr.io_signature2(2,2,gr.sizeof_gr_complex*vlen,
gr.sizeof_char))
frame_size = config.frame_data_part + config.training_data.fbmc_no_preambles/2
print "frame_size: ", frame_size
ft = [0] * frame_size
ft[0] = 1
# The next block ensures that only complete frames find their way into
# the old outer receiver. The dynamic frame start trigger is hence
# replaced with a static one, fixed to the frame length.
frame_sampler = ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc,
frame_size )
symbol_output = blocks.vector_to_stream( gr.sizeof_gr_complex * total_subc,
frame_size )
#delayed_frame_start = blocks.delay( gr.sizeof_char, config.frame_length-1 - config.training_data.fbmc_no_preambles/2 )
delayed_frame_start = blocks.delay( gr.sizeof_char, config.frame_length/2-1)
damn_static_frame_trigger = blocks.vector_source_b( ft, True )
#oqam_postpro = ofdm.fbmc_oqam_postprocessing_vcvc(total_subc,0,0)
self.connect( self, frame_sampler, symbol_output ,self)
#self.connect( (self,1), blocks.keep_m_in_n(gr.sizeof_char,config.frame_data_part + config.training_data.fbmc_no_preambles/2,2*config.frame_data_part + config.training_data.fbmc_no_preambles,0),delayed_frame_start, ( frame_sampler, 1 ) )
self.connect( (self,1), delayed_frame_start, ( frame_sampler, 1 ) )
#self.connect( self, blocks.multiply_const_vcc(([1.0]*total_subc)) ,self)
#terminate_stream(self,frame_sampler)
self.connect( damn_static_frame_trigger, (self,1) )
def __init__(self, vlen):
gr.hier_block2.__init__(
self, "snr_estimator",
gr.io_signature2(2, 2, gr.sizeof_gr_complex, gr.sizeof_char),
gr.io_signature(1, 1, gr.sizeof_float))
data_in = (self, 0)
trig_in = (self, 1)
snr_out = (self, 0)
## Preamble Extraction
sampler = vector_sampler(gr.sizeof_gr_complex, vlen)
self.connect(data_in, sampler)
self.connect(trig_in, (sampler, 1))
## Algorithm implementation
estim = sc_snr_estimator(vlen)
self.connect(sampler, estim)
self.connect(estim, snr_out)
return
## Split block into two parts
splitter = gr.vector_to_streams(gr.sizeof_gr_complex * vlen / 2, 2)
self.connect(sampler, splitter)
## Conjugate first half block
conj = gr.conjugate_cc(vlen / 2)
self.connect(splitter, conj)
## Vector multiplication of both half blocks
vmult = gr.multiply_vcc(vlen / 2)
self.connect(conj, vmult)
self.connect((splitter, 1), (vmult, 1))
## Sum of Products
psum = vector_sum_vcc(vlen / 2)
self.connect(vmult, psum)
## Magnitude of P(d)
p_mag = gr.complex_to_mag()
self.connect(psum, p_mag)
## Squared Magnitude of block
r_magsqrd = gr.complex_to_mag_squared(vlen)
self.connect(sampler, r_magsqrd)
## Sum of squared second half block
r_sum = vector_sum_vff(vlen)
self.connect(r_magsqrd, r_sum)
## Square Root of Metric
m_sqrt = gr.divide_ff()
self.connect(p_mag, (m_sqrt, 0))
self.connect(r_sum, gr.multiply_const_ff(0.5), (m_sqrt, 1))
## Denominator of SNR estimate
denom = gr.add_const_ff(1)
neg_m_sqrt = gr.multiply_const_ff(-1.0)
self.connect(m_sqrt, limit_vff(1, 1 - 2e-5, -1000), neg_m_sqrt, denom)
## SNR estimate
snr_est = gr.divide_ff()
self.connect(m_sqrt, (snr_est, 0))
self.connect(denom, (snr_est, 1))
## Setup Output Connections
self.connect(snr_est, self)
def __init__(self):
gr.top_block.__init__(self, "Top Block")
Qt.QWidget.__init__(self)
self.setWindowTitle("Top Block")
try:
self.setWindowIcon(Qt.QIcon.fromTheme('gnuradio-grc'))
except:
pass
self.top_scroll_layout = Qt.QVBoxLayout()
self.setLayout(self.top_scroll_layout)
self.top_scroll = Qt.QScrollArea()
self.top_scroll.setFrameStyle(Qt.QFrame.NoFrame)
self.top_scroll_layout.addWidget(self.top_scroll)
self.top_scroll.setWidgetResizable(True)
self.top_widget = Qt.QWidget()
self.top_scroll.setWidget(self.top_widget)
self.top_layout = Qt.QVBoxLayout(self.top_widget)
self.top_grid_layout = Qt.QGridLayout()
self.top_layout.addLayout(self.top_grid_layout)
self.settings = Qt.QSettings("GNU Radio", "top_block")
self.restoreGeometry(self.settings.value("geometry").toByteArray())
##################################################
# Variables
##################################################
self.used_id_bits = used_id_bits = 8
self.subcarriers = subcarriers = 208
self.id_blocks = id_blocks = 1
self.fft_length = fft_length = 256
self.fbmc = fbmc = 1
self.estimation_preamble = estimation_preamble = 0
self.data_blocks = data_blocks = 10
self.training_data = training_data = default_block_header(subcarriers,fft_length,fbmc,estimation_preamble,[])
self.repeated_id_bits = repeated_id_bits = subcarriers/used_id_bits
self.data_part = data_part = data_blocks + id_blocks
self.whitener_seed = whitener_seed = seed(1)
self.whitener_pn = whitener_pn = [randint(0,1) for i in range(used_id_bits*repeated_id_bits)]
self.variable_function_probe_2 = variable_function_probe_2 = 0
self.variable_function_probe_1 = variable_function_probe_1 = 0
self.variable_function_probe_0 = variable_function_probe_0 = 0
self.tx_hostname = tx_hostname = "localhost"
self.samp_rate = samp_rate = 4*250000
self.interleaver = interleaver = trellis.interleaver(2000,666)
self.frame_length = frame_length = 2*data_part + training_data.fbmc_no_preambles
self.filter_length = filter_length = 4
self.disable_freq_sync = disable_freq_sync = 1
self.coding = coding = 1
self.chunkdivisor = chunkdivisor = int(numpy.ceil(data_blocks/5.0))
self.ber_window = ber_window = 100000
self.amplitude = amplitude = 1
self.SNR = SNR = 40
##################################################
# Blocks
##################################################
self._amplitude_layout = Qt.QVBoxLayout()
self._amplitude_tool_bar = Qt.QToolBar(self)
self._amplitude_layout.addWidget(self._amplitude_tool_bar)
self._amplitude_tool_bar.addWidget(Qt.QLabel("amplitude"+": "))
class qwt_counter_pyslot(Qwt.QwtCounter):
def __init__(self, parent=None):
Qwt.QwtCounter.__init__(self, parent)
@pyqtSlot('double')
def setValue(self, value):
super(Qwt.QwtCounter, self).setValue(value)
self._amplitude_counter = qwt_counter_pyslot()
self._amplitude_counter.setRange(0, 1, 0.02)
self._amplitude_counter.setNumButtons(2)
self._amplitude_counter.setValue(self.amplitude)
self._amplitude_tool_bar.addWidget(self._amplitude_counter)
self._amplitude_counter.valueChanged.connect(self.set_amplitude)
self._amplitude_slider = Qwt.QwtSlider(None, Qt.Qt.Horizontal, Qwt.QwtSlider.BottomScale, Qwt.QwtSlider.BgSlot)
self._amplitude_slider.setRange(0, 1, 0.02)
self._amplitude_slider.setValue(self.amplitude)
self._amplitude_slider.setMinimumWidth(200)
self._amplitude_slider.valueChanged.connect(self.set_amplitude)
self._amplitude_layout.addWidget(self._amplitude_slider)
self.top_layout.addLayout(self._amplitude_layout)
self.tx_rpc_manager_0 = tx_rpc_manager(fft_length, subcarriers, data_blocks, frame_length, 0, 0.0, samp_rate)
self.tigr_transmit_control_0 = tigr_transmit_control(
subcarriers=subcarriers,
fft_length=fft_length,
used_id_bits=used_id_bits,
estimation_preamble=estimation_preamble,
filter_length=filter_length,
fbmc=fbmc,
data_blocks=data_blocks,
data_part=data_part,
repeated_id_bits=repeated_id_bits,
coding=coding,
)
self.tigr_scatterplot_0 = tigr_scatterplot(
subcarriers=subcarriers,
fbmc=fbmc,
fft_length=fft_length,
estimation_preamble=estimation_preamble,
data_blocks=data_blocks,
data_part=11,
frame_length=frame_length,
)
self.rx_rpc_manager_0 = rx_rpc_manager()
self.rms = fbmc_rms_amplifier(amplitude, subcarriers)
self.zeromq_pub_sink_1 = zeromq.pub_sink(gr.sizeof_float, subcarriers, "tcp://*:5559", 100)
self.zeromq_pub_sink_0 = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557", 100)
def _variable_function_probe_2_probe():
while True:
val = self.rx_rpc_manager_0.add_set_scatter_subcarrier_interface(self.tigr_scatterplot_0.ofdm_vector_element_0.set_element)
try:
self.set_variable_function_probe_2(val)
except AttributeError:
pass
time.sleep(1.0 / (0.000000001))
_variable_function_probe_2_thread = threading.Thread(target=_variable_function_probe_2_probe)
_variable_function_probe_2_thread.daemon = True
_variable_function_probe_2_thread.start()
def _variable_function_probe_1_probe():
while True:
val = self.tx_rpc_manager_0.add_tx_modulation_interface(self.tigr_transmit_control_0.ofdm_allocation_src_0.set_allocation)
try:
self.set_variable_function_probe_1(val)
except AttributeError:
pass
time.sleep(1.0 / (0.000000001))
_variable_function_probe_1_thread = threading.Thread(target=_variable_function_probe_1_probe)
_variable_function_probe_1_thread.daemon = True
_variable_function_probe_1_thread.start()
def _variable_function_probe_0_probe():
while True:
val = self.tx_rpc_manager_0.add_tx_ampl_interface(self.rms.set_rms_amplitude)
try:
self.set_variable_function_probe_0(val)
except AttributeError:
pass
time.sleep(1.0 / (0.000000001))
_variable_function_probe_0_thread = threading.Thread(target=_variable_function_probe_0_probe)
_variable_function_probe_0_thread.daemon = True
_variable_function_probe_0_thread.start()
self.trellis_permutation_0 = trellis.permutation(interleaver.K(), (interleaver.DEINTER()), 1, gr.sizeof_float*1)
self.tigr_fbmc_snr_estimator_0 = tigr_fbmc_snr_estimator(
subcarriers=subcarriers,
fbmc=fbmc,
fft_length=fft_length,
estimation_preamble=estimation_preamble,
frame_length=frame_length,
)
self.tigr_fbmc_inner_receiver_0 = tigr_fbmc_inner_receiver(
subcarriers=subcarriers,
fft_length=fft_length,
data_blocks=data_blocks,
estimation_preamble=estimation_preamble,
filter_length=filter_length,
frame_length=frame_length,
disable_freq_sync=disable_freq_sync,
)
self.tigr_ber_measurement_0 = tigr_ber_measurement(
subcarriers=subcarriers,
fbmc=fbmc,
fft_length=fft_length,
estimation_preamble=estimation_preamble,
ber_window=ber_window,
data_blocks=data_blocks,
)
self.single_pole_iir_filter_xx_0 = filter.single_pole_iir_filter_ff(0.1, subcarriers)
self.ofdm_viterbi_combined_fb_0 = ofdm.viterbi_combined_fb(ofdm.fsm(ofdm.fsm(1,2,[91,121])), subcarriers, -1, -1, 2, chunkdivisor, ([-1,-1,-1,1,1,-1,1,1]), ofdm.TRELLIS_EUCLIDEAN)
self.ofdm_vector_sampler_0 = ofdm.vector_sampler(gr.sizeof_gr_complex*subcarriers, 1)
self.ofdm_vector_padding_0 = ofdm.vector_padding(subcarriers, fft_length, -1)
self.ofdm_multiply_frame_fc_0 = ofdm.multiply_frame_fc(data_part, subcarriers)
self.ofdm_multiply_const_ii_0 = ofdm.multiply_const_ii(1./int(numpy.ceil(data_blocks/5.0)))
self.ofdm_generic_softdemapper_vcf_0 = ofdm.generic_softdemapper_vcf(subcarriers, data_part, 1)
self.ofdm_fbmc_separate_vcvc_1 = ofdm.fbmc_separate_vcvc(fft_length, 2)
self.ofdm_fbmc_polyphase_network_vcvc_1 = ofdm.fbmc_polyphase_network_vcvc(fft_length, filter_length, filter_length*fft_length-1, False)
self.ofdm_fbmc_polyphase_network_vcvc_0 = ofdm.fbmc_polyphase_network_vcvc(fft_length, filter_length, filter_length*fft_length-1, False)
self.ofdm_fbmc_pilot_block_inserter_0 = fbmc_pilot_block_inserter(subcarriers, data_part, training_data, 5)
self.ofdm_fbmc_pilot_block_filter_0 = fbmc_pilot_block_filter(subcarriers, frame_length, data_part, training_data)
self.ofdm_fbmc_overlapping_parallel_to_serial_vcc_0 = ofdm.fbmc_overlapping_parallel_to_serial_vcc(fft_length)
self.ofdm_fbmc_oqam_preprocessing_vcvc_0 = ofdm.fbmc_oqam_preprocessing_vcvc(subcarriers, 0, 0)
self.ofdm_fbmc_frame_sampler_0 = fbmc_frame_sampler(subcarriers, frame_length, data_part, training_data)
self.ofdm_fbmc_beta_multiplier_vcvc_0 = ofdm.fbmc_beta_multiplier_vcvc(fft_length, filter_length, fft_length*fft_length-1, 0)
self.ofdm_dynamic_trigger_ib_0 = ofdm.dynamic_trigger_ib(0)
self.ofdm_depuncture_ff_0 = ofdm.depuncture_ff(subcarriers, 0)
self.ofdm_coded_bpsk_soft_decoder_0 = ofdm.coded_bpsk_soft_decoder(subcarriers, used_id_bits, (whitener_pn))
self.ofdm_allocation_buffer_0 = ofdm.allocation_buffer(subcarriers, data_blocks, "tcp://"+tx_hostname+":3333", 1)
self.fft_vxx_1 = fft.fft_vcc(fft_length, False, ([]), True, 1)
self.channels_channel_model_0 = channels.channel_model(
noise_voltage=math.sqrt(1.0*fft_length/subcarriers)*math.sqrt(0.5)*10**(-SNR/20.0),
frequency_offset=0.0/fft_length,
epsilon=1,
taps=((1.0 ), ),
noise_seed=0,
block_tags=False
)
self.blocks_vector_source_x_0 = blocks.vector_source_b([1] + [0]*(data_blocks/2-1), True, 1, [])
self.blocks_throttle_0 = blocks.throttle(gr.sizeof_gr_complex*1, samp_rate,True)
self.blocks_keep_one_in_n_1 = blocks.keep_one_in_n(gr.sizeof_float*subcarriers, 20)
self.blks2_selector_0 = grc_blks2.selector(
item_size=gr.sizeof_float*1,
num_inputs=2,
num_outputs=1,
input_index=0,
output_index=0,
)
##################################################
# Connections
##################################################
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_0, 0), (self.ofdm_fbmc_overlapping_parallel_to_serial_vcc_0, 0))
self.connect((self.ofdm_fbmc_polyphase_network_vcvc_1, 0), (self.ofdm_fbmc_overlapping_parallel_to_serial_vcc_0, 1))
self.connect((self.ofdm_fbmc_separate_vcvc_1, 1), (self.ofdm_fbmc_polyphase_network_vcvc_1, 0))
self.connect((self.ofdm_fbmc_oqam_preprocessing_vcvc_0, 0), (self.ofdm_fbmc_pilot_block_inserter_0, 0))
self.connect((self.ofdm_fbmc_pilot_block_inserter_0, 0), (self.ofdm_vector_padding_0, 0))
self.connect((self.ofdm_fbmc_beta_multiplier_vcvc_0, 0), (self.fft_vxx_1, 0))
self.connect((self.fft_vxx_1, 0), (self.ofdm_fbmc_separate_vcvc_1, 0))
self.connect((self.tigr_transmit_control_0, 0), (self.ofdm_fbmc_oqam_preprocessing_vcvc_0, 0))
self.connect((self.single_pole_iir_filter_xx_0, 0), (self.blocks_keep_one_in_n_1, 0))
self.connect((self.ofdm_fbmc_frame_sampler_0, 1), (self.ofdm_fbmc_pilot_block_filter_0, 1))
self.connect((self.ofdm_fbmc_frame_sampler_0, 0), (self.ofdm_fbmc_pilot_block_filter_0, 0))
self.connect((self.ofdm_fbmc_pilot_block_filter_0, 1), (self.ofdm_vector_sampler_0, 1))
self.connect((self.ofdm_vector_sampler_0, 0), (self.ofdm_coded_bpsk_soft_decoder_0, 0))
self.connect((self.ofdm_coded_bpsk_soft_decoder_0, 0), (self.ofdm_allocation_buffer_0, 0))
self.connect((self.ofdm_allocation_buffer_0, 1), (self.ofdm_generic_softdemapper_vcf_0, 1))
self.connect((self.single_pole_iir_filter_xx_0, 0), (self.ofdm_generic_softdemapper_vcf_0, 2))
self.connect((self.ofdm_generic_softdemapper_vcf_0, 0), (self.trellis_permutation_0, 0))
self.connect((self.ofdm_depuncture_ff_0, 0), (self.ofdm_viterbi_combined_fb_0, 0))
self.connect((self.ofdm_allocation_buffer_0, 1), (self.ofdm_depuncture_ff_0, 1))
self.connect((self.blocks_vector_source_x_0, 0), (self.ofdm_depuncture_ff_0, 2))
self.connect((self.ofdm_allocation_buffer_0, 0), (self.ofdm_multiply_const_ii_0, 0))
self.connect((self.ofdm_multiply_const_ii_0, 0), (self.ofdm_viterbi_combined_fb_0, 1))
self.connect((self.ofdm_fbmc_separate_vcvc_1, 0), (self.ofdm_fbmc_polyphase_network_vcvc_0, 0))
self.connect((self.ofdm_viterbi_combined_fb_0, 0), (self.tigr_ber_measurement_0, 2))
self.connect((self.ofdm_dynamic_trigger_ib_0, 0), (self.tigr_ber_measurement_0, 3))
self.connect((self.ofdm_fbmc_frame_sampler_0, 0), (self.tigr_fbmc_snr_estimator_0, 0))
self.connect((self.ofdm_fbmc_frame_sampler_0, 1), (self.tigr_fbmc_snr_estimator_0, 1))
self.connect((self.tigr_fbmc_inner_receiver_0, 1), (self.ofdm_fbmc_frame_sampler_0, 1))
self.connect((self.tigr_fbmc_inner_receiver_0, 2), (self.ofdm_fbmc_frame_sampler_0, 0))
self.connect((self.rms, 0), (self.blocks_throttle_0, 0))
self.connect((self.tigr_fbmc_inner_receiver_0, 3), (self.zeromq_pub_sink_0, 0))
self.connect((self.blocks_keep_one_in_n_1, 0), (self.zeromq_pub_sink_1, 0))
self.connect((self.ofdm_vector_padding_0, 0), (self.ofdm_fbmc_beta_multiplier_vcvc_0, 0))
self.connect((self.tigr_fbmc_inner_receiver_0, 0), (self.single_pole_iir_filter_xx_0, 0))
self.connect((self.ofdm_fbmc_overlapping_parallel_to_serial_vcc_0, 0), (self.rms, 0))
self.connect((self.ofdm_allocation_buffer_0, 0), (self.ofdm_dynamic_trigger_ib_0, 0))
self.connect((self.ofdm_coded_bpsk_soft_decoder_0, 0), (self.tigr_ber_measurement_0, 0))
self.connect((self.ofdm_allocation_buffer_0, 0), (self.tigr_ber_measurement_0, 1))
self.connect((self.blks2_selector_0, 0), (self.ofdm_depuncture_ff_0, 0))
self.connect((self.trellis_permutation_0, 0), (self.blks2_selector_0, 1))
self.connect((self.ofdm_generic_softdemapper_vcf_0, 0), (self.blks2_selector_0, 0))
self.connect((self.blocks_throttle_0, 0), (self.channels_channel_model_0, 0))
self.connect((self.channels_channel_model_0, 0), (self.tigr_fbmc_inner_receiver_0, 0))
self.connect((self.ofdm_fbmc_pilot_block_filter_0, 0), (self.ofdm_vector_sampler_0, 0))
self.connect((self.ofdm_allocation_buffer_0, 2), (self.ofdm_multiply_frame_fc_0, 1))
self.connect((self.ofdm_fbmc_pilot_block_filter_0, 0), (self.ofdm_multiply_frame_fc_0, 0))
self.connect((self.ofdm_multiply_frame_fc_0, 0), (self.tigr_scatterplot_0, 0))
self.connect((self.ofdm_multiply_frame_fc_0, 0), (self.ofdm_generic_softdemapper_vcf_0, 0))
def __init__(self, fft_length, block_length, block_header, range, options):
gr.hier_block2.__init__(self, "integer_fo_estimator",
gr.io_signature3(3,3,gr.sizeof_gr_complex,gr.sizeof_float,gr.sizeof_char),
gr.io_signature2(3,3,gr.sizeof_float,gr.sizeof_char))
raise NotImplementedError,"Obsolete class"
self._range = range
# threshold after integer part frequency offset estimation
# if peak value below threshold, assume false triggering
self._thr_lo = 0.4 #0.19 # empirically found threshold. see ioe_metric.float
self._thr_hi = 0.4 #0.2
# stuff to be removed after bugfix for hierblock2s
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.time_sync = gr.kludge_copy(gr.sizeof_char)
self.epsilon = (self,1)
self.connect((self,0),self.input)
self.connect((self,2),self.time_sync)
delay(gr.sizeof_char,
block_header.schmidl_fine_sync[0]*block_length)
# sample ofdm symbol (preamble 1 and 2)
sampler_symbol1 = vector_sampler(gr.sizeof_gr_complex,fft_length)
sampler_symbol2 = vector_sampler(gr.sizeof_gr_complex,fft_length)
time_delay1 = delay(gr.sizeof_char,block_length*block_header.schmidl_fine_sync[1])
self.connect(self.input, (sampler_symbol1,0))
self.connect(self.input, (sampler_symbol2,0))
if block_header.schmidl_fine_sync[0] > 0:
time_delay0 = delay(gr.sizeof_char,block_length*block_header.schmidl_fine_sync[0])
self.connect(self.time_sync, time_delay0, (sampler_symbol1,1))
else:
self.connect(self.time_sync, (sampler_symbol1,1))
self.connect(self.time_sync, time_delay1, (sampler_symbol2,1))
# negative fractional frequency offset estimate
epsilon = gr.multiply_const_ff(-1.0)
self.connect(self.epsilon, epsilon)
# compensate for fractional frequency offset on per symbol base
# freq_shift: vector length, modulator sensitivity
# freq_shift third input: reset phase accumulator
# symbol/preamble 1
freq_shift_sym1 = frequency_shift_vcc(fft_length, 1.0/fft_length)
self.connect(sampler_symbol1, (freq_shift_sym1,0))
self.connect(epsilon, (freq_shift_sym1,1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym1,2))
# symbol/preamble 2
freq_shift_sym2 = frequency_shift_vcc(fft_length, 1.0/fft_length)
self.connect(sampler_symbol2, (freq_shift_sym2,0))
self.connect(epsilon, (freq_shift_sym2,1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym2,2))
# fourier transfrom on both preambles
fft_sym1 = gr.fft_vcc(fft_length, True, [], True) # Forward + Blockshift
fft_sym2 = gr.fft_vcc(fft_length, True, [], True) # Forward + Blockshift
# calculate schmidl's metric for estimation of freq. offset's integer part
assert(hasattr(block_header, "schmidl_fine_sync"))
pre1 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[0]]
pre2 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[1]]
diff_pn = concatenate([[conjugate(math.sqrt(2)*pre2[2*i]/pre1[2*i]),0.0j] for i in arange(len(pre1)/2)])
cfo_estimator = schmidl_cfo_estimator(fft_length, len(pre1),
self._range, diff_pn)
self.connect(freq_shift_sym1, fft_sym1, (cfo_estimator,0)) # preamble 1
self.connect(freq_shift_sym2, fft_sym2, (cfo_estimator,1)) # preamble 2
# search for maximum and its argument in interval [-range .. +range]
#arg_max = arg_max_vff(2*self._range + 1)
arg_max_s = gr.argmax_fs(2*self._range+1)
arg_max = gr.short_to_float()
ifo_max = gr.max_ff(2*self._range + 1) # vlen
ifo_estimate = gr.add_const_ff(-self._range)
self.connect(cfo_estimator, arg_max_s, arg_max, ifo_estimate)
self.connect(cfo_estimator, ifo_max)
self.connect((arg_max_s,1),gr.null_sink(gr.sizeof_short))
# threshold maximal value
ifo_threshold = gr.threshold_ff(self._thr_lo, self._thr_hi, 0.0)
ifo_thr_f2b = gr.float_to_char()
self.connect(ifo_max, ifo_threshold, ifo_thr_f2b)
# gating the streams ifo_estimate (integer part) and epsilon (frac. part)
# if the metric's peak value was above the chosen threshold, assume to have
# found a new burst. peak value below threshold results in blocking the
# streams
self.gate = gate_ff()
self.connect(ifo_thr_f2b, (self.gate,0)) # threshold stream
self.connect(ifo_estimate, (self.gate,1))
self.connect(epsilon, (self.gate,2))
# peak filtering
# resynchronize and suppress peaks that didn't match a preamble
filtered_time_sync = peak_resync_bb(True) # replace
self.connect(self.time_sync, (filtered_time_sync,0))
self.connect(ifo_thr_f2b, (filtered_time_sync,1))
# find complete estimation for frequency offset
# add together fractional and integer part
freq_offset = gr.add_ff()
self.connect((self.gate,1), gr.multiply_const_ff(-1.0), (freq_offset,0)) # integer offset
self.connect((self.gate,2), (freq_offset,1)) # frac offset
# output connections
self.connect(freq_offset, (self,0))
self.connect(filtered_time_sync, (self,1))
self.connect((self.gate,0), (self,2)) # used for frame trigger
#########################################
# debugging
if options.log:
self.epsilon2_sink = gr.vector_sink_f()
self.connect(epsilon, self.epsilon2_sink)
self.connect(cfo_estimator, gr.file_sink(gr.sizeof_float*(self._range*2+1), "data/ioe_metric.float"))
# output joint stream
preamble_stream = gr.streams_to_vector(fft_length * gr.sizeof_gr_complex, 2)
self.connect(fft_sym1, (preamble_stream,0))
self.connect(fft_sym2, (preamble_stream,1))
self.connect(preamble_stream, gr.file_sink(gr.sizeof_gr_complex * 2 * fft_length, "data/preambles.compl"))
# output, preambles before and after correction, magnitude and complex spectrum
self.connect(sampler_symbol1, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length, "data/pre1_bef.compl"))
self.connect(sampler_symbol1, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length, "data/pre1_bef.float"))
self.connect(sampler_symbol2, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length, "data/pre2_bef.compl"))
self.connect(sampler_symbol2, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length, "data/pre2_bef.float"))
self.connect(freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length,"data/pre1.compl"))
self.connect(freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length,"data/pre1.float"))
self.connect(freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length,"data/pre2.compl"))
self.connect(freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length,"data/pre2.float"))
# calculate epsilon from corrected source to check function
test_cp = cyclic_prefixer(fft_length, block_length)
test_eps = foe(fft_length)
self.connect(freq_shift_sym1, test_cp, test_eps, gr.file_sink(gr.sizeof_float, "data/eps_after.float"))
try:
gr.hier_block.update_var_names(self, "ifo_estimator", vars())
gr.hier_block.update_var_names(self, "ifo_estimator", vars(self))
except:
pass
def __init__(self, fft_length, block_length, block_header, range, options):
gr.hier_block2.__init__(
self, "integer_fo_estimator",
gr.io_signature3(3, 3, gr.sizeof_gr_complex, gr.sizeof_float,
gr.sizeof_char),
gr.io_signature2(3, 3, gr.sizeof_float, gr.sizeof_char))
raise NotImplementedError, "Obsolete class"
self._range = range
# threshold after integer part frequency offset estimation
# if peak value below threshold, assume false triggering
self._thr_lo = 0.4 #0.19 # empirically found threshold. see ioe_metric.float
self._thr_hi = 0.4 #0.2
# stuff to be removed after bugfix for hierblock2s
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.time_sync = gr.kludge_copy(gr.sizeof_char)
self.epsilon = (self, 1)
self.connect((self, 0), self.input)
self.connect((self, 2), self.time_sync)
delay(gr.sizeof_char, block_header.schmidl_fine_sync[0] * block_length)
# sample ofdm symbol (preamble 1 and 2)
sampler_symbol1 = vector_sampler(gr.sizeof_gr_complex, fft_length)
sampler_symbol2 = vector_sampler(gr.sizeof_gr_complex, fft_length)
time_delay1 = delay(gr.sizeof_char,
block_length * block_header.schmidl_fine_sync[1])
self.connect(self.input, (sampler_symbol1, 0))
self.connect(self.input, (sampler_symbol2, 0))
if block_header.schmidl_fine_sync[0] > 0:
time_delay0 = delay(
gr.sizeof_char,
block_length * block_header.schmidl_fine_sync[0])
self.connect(self.time_sync, time_delay0, (sampler_symbol1, 1))
else:
self.connect(self.time_sync, (sampler_symbol1, 1))
self.connect(self.time_sync, time_delay1, (sampler_symbol2, 1))
# negative fractional frequency offset estimate
epsilon = gr.multiply_const_ff(-1.0)
self.connect(self.epsilon, epsilon)
# compensate for fractional frequency offset on per symbol base
# freq_shift: vector length, modulator sensitivity
# freq_shift third input: reset phase accumulator
# symbol/preamble 1
freq_shift_sym1 = frequency_shift_vcc(fft_length, 1.0 / fft_length)
self.connect(sampler_symbol1, (freq_shift_sym1, 0))
self.connect(epsilon, (freq_shift_sym1, 1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym1, 2))
# symbol/preamble 2
freq_shift_sym2 = frequency_shift_vcc(fft_length, 1.0 / fft_length)
self.connect(sampler_symbol2, (freq_shift_sym2, 0))
self.connect(epsilon, (freq_shift_sym2, 1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym2, 2))
# fourier transfrom on both preambles
fft_sym1 = gr.fft_vcc(fft_length, True, [],
True) # Forward + Blockshift
fft_sym2 = gr.fft_vcc(fft_length, True, [],
True) # Forward + Blockshift
# calculate schmidl's metric for estimation of freq. offset's integer part
assert (hasattr(block_header, "schmidl_fine_sync"))
pre1 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[0]]
pre2 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[1]]
diff_pn = concatenate(
[[conjugate(math.sqrt(2) * pre2[2 * i] / pre1[2 * i]), 0.0j]
for i in arange(len(pre1) / 2)])
cfo_estimator = schmidl_cfo_estimator(fft_length, len(pre1),
self._range, diff_pn)
self.connect(freq_shift_sym1, fft_sym1,
(cfo_estimator, 0)) # preamble 1
self.connect(freq_shift_sym2, fft_sym2,
(cfo_estimator, 1)) # preamble 2
# search for maximum and its argument in interval [-range .. +range]
#arg_max = arg_max_vff(2*self._range + 1)
arg_max_s = gr.argmax_fs(2 * self._range + 1)
arg_max = gr.short_to_float()
ifo_max = gr.max_ff(2 * self._range + 1) # vlen
ifo_estimate = gr.add_const_ff(-self._range)
self.connect(cfo_estimator, arg_max_s, arg_max, ifo_estimate)
self.connect(cfo_estimator, ifo_max)
self.connect((arg_max_s, 1), gr.null_sink(gr.sizeof_short))
# threshold maximal value
ifo_threshold = gr.threshold_ff(self._thr_lo, self._thr_hi, 0.0)
ifo_thr_f2b = gr.float_to_char()
self.connect(ifo_max, ifo_threshold, ifo_thr_f2b)
# gating the streams ifo_estimate (integer part) and epsilon (frac. part)
# if the metric's peak value was above the chosen threshold, assume to have
# found a new burst. peak value below threshold results in blocking the
# streams
self.gate = gate_ff()
self.connect(ifo_thr_f2b, (self.gate, 0)) # threshold stream
self.connect(ifo_estimate, (self.gate, 1))
self.connect(epsilon, (self.gate, 2))
# peak filtering
# resynchronize and suppress peaks that didn't match a preamble
filtered_time_sync = peak_resync_bb(True) # replace
self.connect(self.time_sync, (filtered_time_sync, 0))
self.connect(ifo_thr_f2b, (filtered_time_sync, 1))
# find complete estimation for frequency offset
# add together fractional and integer part
freq_offset = gr.add_ff()
self.connect((self.gate, 1), gr.multiply_const_ff(-1.0),
(freq_offset, 0)) # integer offset
self.connect((self.gate, 2), (freq_offset, 1)) # frac offset
# output connections
self.connect(freq_offset, (self, 0))
self.connect(filtered_time_sync, (self, 1))
self.connect((self.gate, 0), (self, 2)) # used for frame trigger
#########################################
# debugging
if options.log:
self.epsilon2_sink = gr.vector_sink_f()
self.connect(epsilon, self.epsilon2_sink)
self.connect(
cfo_estimator,
gr.file_sink(gr.sizeof_float * (self._range * 2 + 1),
"data/ioe_metric.float"))
# output joint stream
preamble_stream = gr.streams_to_vector(
fft_length * gr.sizeof_gr_complex, 2)
self.connect(fft_sym1, (preamble_stream, 0))
self.connect(fft_sym2, (preamble_stream, 1))
self.connect(
preamble_stream,
gr.file_sink(gr.sizeof_gr_complex * 2 * fft_length,
"data/preambles.compl"))
# output, preambles before and after correction, magnitude and complex spectrum
self.connect(
sampler_symbol1, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre1_bef.compl"))
self.connect(
sampler_symbol1, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length,
"data/pre1_bef.float"))
self.connect(
sampler_symbol2, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre2_bef.compl"))
self.connect(
sampler_symbol2, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length,
"data/pre2_bef.float"))
self.connect(
freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre1.compl"))
self.connect(
freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length, "data/pre1.float"))
self.connect(
freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True),
gr.file_sink(gr.sizeof_gr_complex * fft_length,
"data/pre2.compl"))
self.connect(
freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True),
gr.complex_to_mag(fft_length),
gr.file_sink(gr.sizeof_float * fft_length, "data/pre2.float"))
# calculate epsilon from corrected source to check function
test_cp = cyclic_prefixer(fft_length, block_length)
test_eps = foe(fft_length)
self.connect(freq_shift_sym1, test_cp, test_eps,
gr.file_sink(gr.sizeof_float, "data/eps_after.float"))
try:
gr.hier_block.update_var_names(self, "ifo_estimator", vars())
gr.hier_block.update_var_names(self, "ifo_estimator", vars(self))
except:
pass
def __init__(self, vlen):
gr.hier_block2.__init__(self, "snr_estimator",
gr.io_signature2(2,2,gr.sizeof_gr_complex,gr.sizeof_char),
gr.io_signature (1,1,gr.sizeof_float))
data_in = (self,0)
trig_in = (self,1)
snr_out = (self,0)
## Preamble Extraction
sampler = vector_sampler(gr.sizeof_gr_complex,vlen)
self.connect(data_in,sampler)
self.connect(trig_in,(sampler,1))
## Algorithm implementation
estim = sc_snr_estimator(vlen)
self.connect(sampler,estim)
self.connect(estim,snr_out)
return
## Split block into two parts
splitter = gr.vector_to_streams(gr.sizeof_gr_complex*vlen/2,2)
self.connect(sampler,splitter)
## Conjugate first half block
conj = gr.conjugate_cc(vlen/2)
self.connect(splitter,conj)
## Vector multiplication of both half blocks
vmult = gr.multiply_vcc(vlen/2)
self.connect(conj,vmult)
self.connect((splitter,1),(vmult,1))
## Sum of Products
psum = vector_sum_vcc(vlen/2)
self.connect(vmult,psum)
## Magnitude of P(d)
p_mag = gr.complex_to_mag()
self.connect(psum,p_mag)
## Squared Magnitude of block
r_magsqrd = gr.complex_to_mag_squared(vlen)
self.connect(sampler,r_magsqrd)
## Sum of squared second half block
r_sum = vector_sum_vff(vlen)
self.connect(r_magsqrd,r_sum)
## Square Root of Metric
m_sqrt = gr.divide_ff()
self.connect(p_mag,(m_sqrt,0))
self.connect(r_sum,gr.multiply_const_ff(0.5),(m_sqrt,1))
## Denominator of SNR estimate
denom = gr.add_const_ff(1)
neg_m_sqrt = gr.multiply_const_ff(-1.0)
self.connect(m_sqrt,limit_vff(1,1-2e-5,-1000),neg_m_sqrt,denom)
## SNR estimate
snr_est = gr.divide_ff()
self.connect(m_sqrt,(snr_est,0))
self.connect(denom,(snr_est,1))
## Setup Output Connections
self.connect(snr_est,self)
def __init__(self, options, log=False):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
#cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
L = block_header.mm_periodic_parts
cp_length = config.cp_length
print "data_subc: ", config.data_subcarriers
print "total_subc: ", config.subcarriers
print "frame_lengthframe_length: ", frame_length
## Set Input/Output signature
gr.hier_block2.__init__(
self,
"fbmc_inner_receiver",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signaturev(
4,
4,
[
gr.sizeof_float * total_subc, # Normalized |CTF|^2
gr.sizeof_char, # Frame start
gr.sizeof_gr_complex * total_subc, # OFDM blocks, SNR est
gr.sizeof_float
])) # CFO
## Input and output ports
self.input = rx_input = self
out_ofdm_blocks = (self, 2)
out_frame_start = (self, 1)
out_disp_ctf = (self, 0)
out_disp_cfo = (self, 3)
#out_snr_pream = ( self, 3 )
## pre-FFT processing
'''
## Compute autocorrelations for S&C preamble
## and cyclic prefix
self._sc_metric = sc_metric = autocorrelator( fft_length/2, fft_length/2 )
self._gi_metric = gi_metric = autocorrelator( fft_length, cp_length )
self.connect( rx_input, sc_metric )
self.connect( rx_input, gi_metric )
terminate_stream(self, gi_metric)
## Sync. Output contains OFDM blocks
sync = ofdm.time_sync( fft_length/2, 1)
self.connect( rx_input, ( sync, 0 ) )
self.connect( sc_metric, ( sync, 1 ) )
self.connect( sc_metric, ( sync, 2 ) )
ofdm_blocks = ( sync, 0 )
frame_start = ( sync, 1 )
log_to_file( self, ( sync, 1 ), "data/fbmc_peak_detector.char" )
'''
if options.ideal is False and options.ideal2 is False:
#Testing old/new metric
self.tm = schmidl.recursive_timing_metric(2 * fft_length)
self.connect(self.input, self.tm)
#log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm.float" )
timingmetric_shift = 0 #-2 #int(-cp_length * 0.8)
tmfilter = filter.fft_filter_fff(
1, [2. / fft_length] * (fft_length / 2)
) # ofdm.lms_fir_ff( fft_length, 1e-3 ) #; filter.fir_filter_fff(1, [1./fft_length]*fft_length)
self.connect(self.tm, tmfilter)
self.tm = tmfilter
#log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm2.float" )
self._pd_thres = 0.6
self._pd_lookahead = fft_length # empirically chosen
peak_detector = ofdm.peak_detector_02_fb(self._pd_lookahead,
self._pd_thres)
self.connect(self.tm, peak_detector)
#log_to_file( self, peak_detector, "data/fbmc_rec_peak_detector.char" )
#frame_start = [0]*frame_length
#frame_start[0] = 1
#frame_start = blocks.vector_source_b(frame_start,True)
#OLD
#delayed_timesync = blocks.delay(gr.sizeof_char,
# (frame_length-10)*fft_length/2 - fft_length/4 -1 + timingmetric_shift)
delayed_timesync = blocks.delay(
gr.sizeof_char,
(frame_length - 10) * fft_length / 2 - fft_length / 4 +
int(2.5 * fft_length) + timingmetric_shift - 1)
#delayed_timesync = blocks.delay(gr.sizeof_char,
#(frame_length-10)*fft_length/2 - fft_length/4 + int(3.5*fft_length) + timingmetric_shift-1)
self.connect(peak_detector, delayed_timesync)
self.block_sampler = ofdm.vector_sampler(
gr.sizeof_gr_complex, fft_length / 2 * frame_length)
self.connect(self.input, self.block_sampler)
self.connect(delayed_timesync, (self.block_sampler, 1))
#log_to_file( self, self.block_sampler, "data/fbmc_block_sampler.compl" )
vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex * fft_length,
frame_length / 2)
self.connect(self.block_sampler, vt2s)
#terminate_stream(self,ofdm_blocks)
ofdm_blocks = vt2s
'''
# TODO: dynamic solution
vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length/2,
frame_length)
self.connect(self.block_sampler,vt2s)
terminate_stream(self,( sync, 0 ))
ofdm_blocks = vt2s
'''
##stv_help = blocks.stream_to_vector(gr.sizeof_gr_complex*config.fft_length/2, 1)
#stv_help = blocks.vector_to_stream(gr.sizeof_gr_complex*config.fft_length/2, 2)
##self.connect(ofdm_blocks, stv_help)
##ofdm_blocks = stv_help
#ofdm_blocks = ( sync, 0 )
#frame_start = ( sync, 1 )
#log_to_file(self, frame_start, "data/frame_start.compl")
#log_to_file( self, sc_metric, "data/sc_metric.float" )
#log_to_file( self, gi_metric, "data/gi_metric.float" )
#log_to_file( self, (sync,1), "data/sync.float" )
# log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
frame_start = [0] * int(frame_length / 2)
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start, True)
#frame_start2 = [0]*int(frame_length/2)
#frame_start2[0] = 1
#frame_start2 = blocks.vector_source_b(frame_start2,True)
if options.disable_time_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, ofdm_blocks)
terminate_stream(self, frame_start)
serial_to_parallel = blocks.stream_to_vector(
gr.sizeof_gr_complex, fft_length)
#discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
#serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
#discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
#self.connect( rx_input,serial_to_parallel)
#self.connect( rx_input, blocks.delay(gr.sizeof_gr_complex,0),serial_to_parallel)
initial_skip = blocks.skiphead(gr.sizeof_gr_complex,
2 * fft_length)
self.connect(rx_input, initial_skip)
if options.ideal is False and options.ideal2 is False:
self.connect(initial_skip, serial_to_parallel)
ofdm_blocks = serial_to_parallel
else:
ofdm_blocks = initial_skip
#self.connect( rx_input, serial_to_parallel, discard_cp )
frame_start = [0] * int(frame_length / 2)
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start, True)
#frame_start2 = [0]*int(frame_length/2)
#frame_start2[0] = 1
#frame_start2 = blocks.vector_source_b(frame_start2,True)
print "Disabled time synchronization stage"
print "\t\t\t\t\tframe_length = ", frame_length
if options.ideal is False and options.ideal2 is False:
## Extract preamble, feed to Morelli & Mengali frequency offset estimator
assert (block_header.mm_preamble_pos == 0)
morelli_foe = ofdm.mm_frequency_estimator(fft_length, 2, 1,
config.fbmc)
sampler_preamble = ofdm.vector_sampler(
gr.sizeof_gr_complex * fft_length, 1)
self.connect(ofdm_blocks, (sampler_preamble, 0))
self.connect(frame_start, blocks.delay(gr.sizeof_char, 1),
(sampler_preamble, 1))
self.connect(sampler_preamble, morelli_foe)
freq_offset = morelli_foe
print "FRAME_LENGTH: ", frame_length
#log_to_file( self, sampler_preamble, "data/sampler_preamble.compl" )
#log_to_file( self, rx_input, "data/rx_input.compl" )
#log_to_file( self, ofdm_blocks, "data/rx_input.compl" )
#Extracting preamble for SNR estimation
#fft_snr_est = fft_blocks.fft_vcc( fft_length, True, [], True )
#self.connect( sampler_preamble, blocks.stream_to_vector(gr.sizeof_gr_complex*fft_length/2, 2), fft_snr_est )
## Remove virtual subcarriers
#if fft_length > data_subc:
#subcarrier_mask_snr_est = ofdm.vector_mask( fft_length, virtual_subc/2,
# total_subc, [] )
#self.connect( fft_snr_est, subcarrier_mask_snr_est )
#fft_snr_est = subcarrier_mask_snr_est
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
#self.connect( fft_snr_est, out_snr_pream ) # Connecting to output
## Adaptive LMS FIR filtering of frequency offset
lms_fir = ofdm.lms_fir_ff(20,
1e-3) # TODO: verify parameter choice
self.connect(freq_offset, lms_fir)
freq_offset = lms_fir
self.connect(freq_offset,
blocks.keep_one_in_n(gr.sizeof_float,
20), out_disp_cfo)
else:
self.connect(blocks.vector_source_f([1]), out_disp_cfo)
#log_to_file(self, lms_fir, "data/lms_fir.float")
if options.disable_freq_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, freq_offset)
freq_offset = blocks.vector_source_f([0.0], True)
print "Disabled frequency synchronization stage"
if options.ideal is False and options.ideal2 is False:
## Correct frequency shift, feed-forward structure
frequency_shift = ofdm.frequency_shift_vcc(fft_length,
-1.0 / fft_length, 0)
#freq_shift = blocks.multiply_cc()
#norm_freq = -0.1 / config.fft_length
#freq_off = self.freq_off_src = analog.sig_source_c(1.0, analog.GR_SIN_WAVE, norm_freq, 1.0, 0.0 )
self.connect(ofdm_blocks, (frequency_shift, 0))
self.connect(freq_offset, (frequency_shift, 1))
self.connect(frame_start, blocks.delay(gr.sizeof_char, 0),
(frequency_shift, 2))
#self.connect(frequency_shift,s2help)
#ofdm_blocks = s2help
ofdm_blocks = frequency_shift
#terminate_stream(self, frequency_shift)
#inner_pb_filt = self._inner_pilot_block_filter = fbmc_inner_pilot_block_filter()
#self.connect(ofdm_blocks,inner_pb_filt)
#self.connect(frame_start,(inner_pb_filt,1))
#self.connect((inner_pb_filt,1),blocks.null_sink(gr.sizeof_char))
#ofdm_blocks = (inner_pb_filt,0)
overlap_ser_to_par = ofdm.fbmc_overlapping_serial_to_parallel_cvc(
fft_length)
self.separate_vcvc = ofdm.fbmc_separate_vcvc(fft_length, 2)
self.polyphase_network_vcvc_1 = ofdm.fbmc_polyphase_network_vcvc(
fft_length, 4, 4 * fft_length - 1, True)
self.polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(
fft_length, 4, 4 * fft_length - 1, True)
self.junction_vcvc = ofdm.fbmc_junction_vcvc(fft_length, 2)
self.fft_fbmc = fft_blocks.fft_vcc(fft_length, True, [], True)
print "config.training_data.fbmc_no_preambles: ", config.training_data.fbmc_no_preambles
#center_preamble = [1, -1j, -1, 1j]
#self.preamble = preamble = [0]*total_subc + center_preamble*((int)(total_subc/len(center_preamble)))+[0]*total_subc
self.preamble = preamble = config.training_data.fbmc_pilotsym_fd_list
#inv_preamble = 1. / numpy.array(self.preamble)
#print "self.preamble: ", len(self.preamble
#print "inv_preamble: ", list(inv_preamble)
#print "self.preamble", self.preamble
#print "self.preamble2", self.preamble2
self.multiply_const = ofdm.multiply_const_vcc(
([1.0 / (math.sqrt(fft_length * 0.6863))] * total_subc))
self.beta_multiplier_vcvc = ofdm.fbmc_beta_multiplier_vcvc(
total_subc, 4, 4 * fft_length - 1, 0)
#self.skiphead = blocks.skiphead(gr.sizeof_gr_complex*total_subc, 2*4-1-1)
self.skiphead = blocks.skiphead(gr.sizeof_gr_complex * total_subc, 2)
self.skiphead_1 = blocks.skiphead(gr.sizeof_gr_complex * total_subc, 0)
#self.remove_preamble_vcvc = ofdm.fbmc_remove_preamble_vcvc(total_subc, config.frame_data_part/2, config.training_data.fbmc_no_preambles*total_subc/2)
#self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(total_subc, config.frame_data_part, 1, 2, 1, 0)
self.oqam_postprocessing_vcvc = ofdm.fbmc_oqam_postprocessing_vcvc(
total_subc, 0, 0)
#log_to_file( self, ofdm_blocks, "data/PRE_FBMC.compl" )
#log_to_file( self, self.fft_fbmc, "data/FFT_FBMC.compl" )
if options.ideal is False and options.ideal2 is False:
self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(
total_subc, config.frame_data_part, 3, 2, 1, 0)
help2 = blocks.keep_one_in_n(gr.sizeof_gr_complex * total_subc,
frame_length)
self.connect((self.subchannel_processing_vcvc, 1), help2)
#log_to_file( self, self.subchannel_processing_vcvc, "data/fbmc_subc.compl" )
#terminate_stream(self, help2)
if options.ideal is False and options.ideal2 is False:
self.connect(
ofdm_blocks,
blocks.vector_to_stream(gr.sizeof_gr_complex, fft_length),
overlap_ser_to_par)
else:
self.connect(ofdm_blocks, overlap_ser_to_par)
self.connect(overlap_ser_to_par, self.separate_vcvc)
self.connect((self.separate_vcvc, 1),
(self.polyphase_network_vcvc_2, 0))
self.connect((self.separate_vcvc, 0),
(self.polyphase_network_vcvc_1, 0))
self.connect((self.polyphase_network_vcvc_1, 0),
(self.junction_vcvc, 0))
self.connect((self.polyphase_network_vcvc_2, 0),
(self.junction_vcvc, 1))
self.connect(self.junction_vcvc, self.fft_fbmc)
ofdm_blocks = self.fft_fbmc
print "config.dc_null: ", config.dc_null
if fft_length > data_subc:
subcarrier_mask_fbmc = ofdm.vector_mask_dc_null(
fft_length, virtual_subc / 2, total_subc, config.dc_null, [])
self.connect(ofdm_blocks, subcarrier_mask_fbmc)
ofdm_blocks = subcarrier_mask_fbmc
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
#log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
self.connect(ofdm_blocks, self.beta_multiplier_vcvc)
ofdm_blocks = self.beta_multiplier_vcvc
#self.connect(ofdm_blocks,self.multiply_const)
#self.connect(self.multiply_const, (self.skiphead, 0))
self.connect(ofdm_blocks, (self.skiphead, 0))
#log_to_file( self, self.skiphead, "data/fbmc_skiphead_4.compl" )
#self.connect(ofdm_blocks, self.multiply_const)
#self.connect(self.multiply_const, self.beta_multiplier_vcvc)
#self.connect((self.beta_multiplier_vcvc, 0), (self.skiphead, 0))
if options.ideal or options.ideal2:
self.connect((self.skiphead, 0), (self.skiphead_1, 0))
else:
self.connect((self.skiphead, 0),
(self.subchannel_processing_vcvc, 0))
self.connect((self.subchannel_processing_vcvc, 0),
(self.skiphead_1, 0))
#log_to_file( self, self.skiphead, "data/fbmc_subc.compl" )
#self.connect((self.skiphead_1, 0),(self.remove_preamble_vcvc, 0))
#self.connect((self.remove_preamble_vcvc, 0), (self.oqam_postprocessing_vcvc, 0))
#ofdm_blocks = self.oqam_postprocessing_vcvc
#log_to_file( self, self.subchannel_processing_vcvc, "data/subc_0.compl" )
#log_to_file( self, (self.subchannel_processing_vcvc,1), "data/subc_1.compl" )
self.connect((self.skiphead_1, 0), (self.oqam_postprocessing_vcvc, 0))
#self.connect((self.oqam_postprocessing_vcvc, 0), (self.remove_preamble_vcvc, 0) )
ofdm_blocks = (self.oqam_postprocessing_vcvc, 0
) #(self.remove_preamble_vcvc, 0)
#log_to_file( self, (self.oqam_postprocessing_vcvc, 0), "data/fbmc_before_remove.compl" )
#log_to_file( self, self.skiphead, "data/SKIP_HEAD_FBMC.compl" )
#log_to_file( self, self.beta_multiplier_vcvc, "data/BETA_REC_FBMC.compl" )
#log_to_file( self, self.oqam_postprocessing_vcvc, "data/REC_OUT_FBMC.compl" )
""" DISABLED OFDM CHANNEL ESTIMATION PREMBLE -> CORRECT LATER to compare FBMC and OFDM channel estimation
#TAKING THE CHANNEL ESTIMATION PREAMBLE
chest_pre_trigger = blocks.delay( gr.sizeof_char, 3 )
sampled_chest_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length/2, 2 )
self.connect( frame_start, chest_pre_trigger )
self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
self.connect( frequency_shift, ( sampled_chest_preamble, 0 ) )
#ofdm_blocks = sampled_chest_preamble
## FFT
fft = fft_blocks.fft_vcc( fft_length, True, [], True )
self.connect( sampled_chest_preamble, fft )
ofdm_blocks_est = fft
log_to_file( self, sampled_chest_preamble, "data/SAMPLED_EST_PREAMBLE.compl" )
log_to_file( self, ofdm_blocks_est, "data/FFT.compl" )
## Remove virtual subcarriers
if fft_length > data_subc:
subcarrier_mask = ofdm.vector_mask( fft_length, virtual_subc/2,
total_subc, [] )
self.connect( ofdm_blocks_est, subcarrier_mask )
ofdm_blocks_est = subcarrier_mask
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
## post-FFT processing
## extract channel estimation preamble from frame
##chest_pre_trigger = blocks.delay( gr.sizeof_char,
##1 )
##sampled_chest_preamble = \
## ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
##self.connect( frame_start, chest_pre_trigger )
##self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
##self.connect( ofdm_blocks, ( sampled_chest_preamble, 0 ) )
## Least Squares estimator for channel transfer function (CTF)
inv_preamble_fd = numpy.array( block_header.pilotsym_fd[
block_header.channel_estimation_pilot[0] ] )
#print "Channel estimation pilot: ", inv_preamble_fd
inv_preamble_fd = 1. / inv_preamble_fd
LS_channel_estimator = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
self.connect( ofdm_blocks_est, LS_channel_estimator )
estimated_CTF = LS_channel_estimator
terminate_stream(self,estimated_CTF)
"""
if options.ideal is False and options.ideal2 is False:
if options.logcir:
log_to_file(self, sampled_chest_preamble, "data/PREAM.compl")
if not options.disable_ctf_enhancer:
if options.logcir:
ifft1 = fft_blocks.fft_vcc(total_subc, False, [], True)
self.connect(
estimated_CTF, ifft1,
gr.null_sink(gr.sizeof_gr_complex * total_subc))
summ1 = ofdm.vector_sum_vcc(total_subc)
c2m = gr.complex_to_mag(total_subc)
self.connect(estimated_CTF, summ1,
gr.null_sink(gr.sizeof_gr_complex))
self.connect(estimated_CTF, c2m,
gr.null_sink(gr.sizeof_float * total_subc))
log_to_file(self, ifft1, "data/CIR1.compl")
log_to_file(self, summ1, "data/CTFsumm1.compl")
log_to_file(self, estimated_CTF, "data/CTF1.compl")
log_to_file(self, c2m, "data/CTFmag1.float")
## MSE enhancer
ctf_mse_enhancer = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
self.connect(estimated_CTF, ctf_mse_enhancer)
# log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
#ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
#null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
#ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
#ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
# total_subc, [] )
#self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )
estimated_CTF = ctf_mse_enhancer
print "Disabled CTF MSE enhancer"
if options.logcir:
ifft2 = fft_blocks.fft_vcc(total_subc, False, [], True)
self.connect(estimated_CTF, ifft2,
gr.null_sink(gr.sizeof_gr_complex * total_subc))
summ2 = ofdm.vector_sum_vcc(total_subc)
c2m2 = gr.complex_to_mag(total_subc)
self.connect(estimated_CTF, summ2,
gr.null_sink(gr.sizeof_gr_complex))
self.connect(estimated_CTF, c2m2,
gr.null_sink(gr.sizeof_float * total_subc))
log_to_file(self, ifft2, "data/CIR2.compl")
log_to_file(self, summ2, "data/CTFsumm2.compl")
log_to_file(self, estimated_CTF, "data/CTF2.compl")
log_to_file(self, c2m2, "data/CTFmag2.float")
## Postprocess the CTF estimate
## CTF -> inverse CTF (for equalizer)
## CTF -> norm |.|^2 (for CTF display)
ctf_postprocess = ofdm.fbmc_postprocess_CTF_estimate(total_subc)
self.connect(help2, ctf_postprocess)
#estimated_SNR = ( ctf_postprocess, 0 )
disp_CTF = (ctf_postprocess, 0)
#self.connect(estimated_SNR,out_snr_pream)
#log_to_file( self, estimated_SNR, "data/fbmc_SNR.float" )
#Disable measured SNR output
#terminate_stream(self, estimated_SNR)
#self.connect(blocks.vector_source_f([10.0],True) ,out_snr_pream)
# if options.disable_equalization or options.ideal:
# terminate_stream(self, inv_estimated_CTF)
# inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
# inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
# self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
# #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
# inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
# self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
# print "Disabled equalization stage"
'''
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print"\t\t\t\t\tnondata_blocks=",nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
nondata_blocks, pilot_subcarriers,0 )
self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
self.connect( frame_start, ( phase_tracking, 2 ) ) ##
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
'''
## Channel Equalizer
##equalizer = ofdm.channel_equalizer( total_subc )
##self.connect( ofdm_blocks, ( equalizer, 0 ) )
##self.connect( inv_estimated_CTF, ( equalizer, 1 ) )
##self.connect( frame_start, ( equalizer, 2 ) )
##ofdm_blocks = equalizer
#log_to_file(self, equalizer,"data/equalizer_siso.compl")
#log_to_file(self, ofdm_blocks, "data/equalizer.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print "\t\t\t\t\tnondata_blocks=", nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
## Output connections
self.connect(ofdm_blocks, out_ofdm_blocks)
self.connect(frame_start, out_frame_start)
if options.ideal is False and options.ideal2 is False:
self.connect(disp_CTF, out_disp_ctf)
else:
self.connect(blocks.vector_source_f([1.0] * total_subc),
blocks.stream_to_vector(gr.sizeof_float, total_subc),
out_disp_ctf)
if log:
log_to_file(self, sc_metric, "data/sc_metric.float")
log_to_file(self, gi_metric, "data/gi_metric.float")
log_to_file(self, morelli_foe, "data/morelli_foe.float")
log_to_file(self, lms_fir, "data/lms_fir.float")
log_to_file(self, sampler_preamble, "data/preamble.compl")
log_to_file(self, sync, "data/sync.compl")
log_to_file(self, frequency_shift, "data/frequency_shift.compl")
log_to_file(self, fft, "data/fft.compl")
log_to_file(self, fft, "data/fft.float", mag=True)
if vars().has_key('subcarrier_mask'):
log_to_file(self, subcarrier_mask,
"data/subcarrier_mask.compl")
log_to_file(self, ofdm_blocks, "data/ofdm_blocks_out.compl")
log_to_file(self,
frame_start,
"data/frame_start.float",
char_to_float=True)
log_to_file(self, sampled_chest_preamble,
"data/sampled_chest_preamble.compl")
log_to_file(self, LS_channel_estimator,
"data/ls_channel_estimator.compl")
log_to_file(self,
LS_channel_estimator,
"data/ls_channel_estimator.float",
mag=True)
if "ctf_mse_enhancer" in locals():
log_to_file(self, ctf_mse_enhancer,
"data/ctf_mse_enhancer.compl")
log_to_file(self,
ctf_mse_enhancer,
"data/ctf_mse_enhancer.float",
mag=True)
log_to_file(self, (ctf_postprocess, 0),
"data/inc_estimated_ctf.compl")
log_to_file(self, (ctf_postprocess, 1), "data/disp_ctf.float")
log_to_file(self, equalizer, "data/equalizer.compl")
log_to_file(self, equalizer, "data/equalizer.float", mag=True)
log_to_file(self, phase_tracking, "data/phase_tracking.compl")
def publish_rx_performance_measure(self):
if self._rx_performance_measure_initialized():
return
self.rx_performance_measure_initialized = True
config = station_configuration()
vlen = config.data_subcarriers
vlen_sinr_sc = config.subcarriers
# self.rx_per_sink = rpsink = rpsink_dummy()
self.setup_ber_measurement()
self.setup_snr_measurement()
self.setup_snr_measurement_2()
ber_mst = self._ber_measuring_tool
if self._options.sinr_est:
sinr_mst = self._sinr_measurement
sinr_mst_2 = self._sinr_measurement_2
else:
snr_mst = self._snr_measurement
snr_mst_2 = self._snr_measurement_2
# 1. frame id
# 2. channel transfer function
ctf = self.filter_ctf()
ctf_2 = self.filter_ctf_2()
self.zmq_probe_ctf = zeromq.pub_sink(gr.sizeof_float,config.data_subcarriers, "tcp://*:5559")
self.zmq_probe_ctf_2 = zeromq.pub_sink(gr.sizeof_float,config.data_subcarriers, "tcp://*:5558")
self.connect(ctf, blocks.keep_one_in_n(gr.sizeof_float*config.data_subcarriers,20) ,self.zmq_probe_ctf)
self.connect(ctf_2, blocks.keep_one_in_n(gr.sizeof_float*config.data_subcarriers,20) ,self.zmq_probe_ctf_2)
# 3. BER
### FIXME HACK
print "Normal BER measurement"
trig_src = dynamic_trigger_ib(False)
self.connect(self.bitcount_src,trig_src)
ber_sampler = vector_sampler(gr.sizeof_float,1)
self.connect(ber_mst,(ber_sampler,0))
self.connect(trig_src,(ber_sampler,1))
if self._options.log:
trig_src_float = gr.char_to_float()
self.connect(trig_src,trig_src_float)
log_to_file(self, trig_src_float , 'data/dynamic_trigger_out.float')
if self._options.sinr_est is False:
self.zmq_probe_ber = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5556")
self.connect(ber_sampler,blocks.keep_one_in_n(gr.sizeof_float,20) ,self.zmq_probe_ber)
self.zmq_probe_snr = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5555")
self.connect(snr_mst,blocks.keep_one_in_n(gr.sizeof_float,20) ,self.zmq_probe_snr)
self.zmq_probe_snr_2 = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5554")
self.connect(snr_mst_2,blocks.keep_one_in_n(gr.sizeof_float,20) ,self.zmq_probe_snr_2)
def __init__(self, options, log=False):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
dc_null = config.dc_null
L = block_header.mm_periodic_parts
## Set Input/Output signature
gr.hier_block2.__init__(
self,
"ofdm_inner_receiver",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signaturev(
4,
4,
[
gr.sizeof_gr_complex * total_subc, # OFDM blocks
gr.sizeof_char, # Frame start
gr.sizeof_float * total_subc,
gr.sizeof_float
])) # Normalized |CTF|^2
## Input and output ports
self.input = rx_input = self
out_ofdm_blocks = (self, 0)
out_frame_start = (self, 1)
out_disp_ctf = (self, 2)
out_disp_cfo = (self, 3)
## pre-FFT processing
if options.ideal is False and options.ideal2 is False:
if options.old_receiver is False:
## Compute autocorrelations for S&C preamble
## and cyclic prefix
self._sc_metric = sc_metric = autocorrelator(
fft_length / 2, fft_length / 2)
self._gi_metric = gi_metric = autocorrelator(
fft_length, cp_length)
self.connect(rx_input, sc_metric)
self.connect(rx_input, gi_metric)
## Sync. Output contains OFDM blocks
sync = ofdm.time_sync(fft_length, cp_length)
self.connect(rx_input, (sync, 0))
self.connect(sc_metric, (sync, 1))
self.connect(gi_metric, (sync, 2))
ofdm_blocks = (sync, 0)
frame_start = (sync, 1)
#log_to_file( self, ( sync, 1 ), "data/peak_detector.char" )
else:
#Testing old/new metric
self.tm = schmidl.recursive_timing_metric(fft_length)
self.connect(self.input, self.tm)
#log_to_file( self, self.tm, "data/rec_sc_metric_ofdm.float" )
timingmetric_shift = -2 #int(-cp_length/4)# 0#-2 #int(-cp_length * 0.8)
tmfilter = filter.fft_filter_fff(1,
[1. / cp_length] * cp_length)
self.connect(self.tm, tmfilter)
self.tm = tmfilter
self._pd_thres = 0.3
self._pd_lookahead = fft_length / 2 # empirically chosen
peak_detector = ofdm.peak_detector_02_fb(
self._pd_lookahead, self._pd_thres)
self.connect(self.tm, peak_detector)
#log_to_file( self, peak_detector, "data/rec_peak_detector.char" )
frame_start = [0] * frame_length
frame_start[0] = 1
frame_start = self.frame_trigger_old = blocks.vector_source_b(
frame_start, True)
delayed_timesync = blocks.delay(
gr.sizeof_char,
(frame_length - 1) * block_length + timingmetric_shift)
self.connect(peak_detector, delayed_timesync)
self.block_sampler = ofdm.vector_sampler(
gr.sizeof_gr_complex, block_length * frame_length)
self.discard_cp = ofdm.vector_mask(block_length, cp_length,
fft_length, [])
self.connect(self.input, self.block_sampler)
self.connect(delayed_timesync, (self.block_sampler, 1))
# TODO: dynamic solution
vt2s = blocks.vector_to_stream(
gr.sizeof_gr_complex * block_length, frame_length)
self.connect(self.block_sampler, vt2s, self.discard_cp)
#terminate_stream(self,ofdm_blocks)
ofdm_blocks = self.discard_cp
# else:
# serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
# discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
# ofdm_blocks = discard_cp
# self.connect( rx_input, serial_to_parallel, discard_cp )
# frame_start = [0]*frame_length
# frame_start[0] = 1
# frame_start = blocks.vector_source_b(frame_start,True)
#
# print "Disabled time synchronization stage"
## Compute autocorrelations for S&C preamble
## and cyclic prefix
#log_to_file( self, sc_metric, "data/sc_metric_ofdm.float" )
#log_to_file(self, frame_start, "data/frame_start.compl")
# log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
if options.disable_time_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, ofdm_blocks)
terminate_stream(self, frame_start)
serial_to_parallel = blocks.stream_to_vector(
gr.sizeof_gr_complex, block_length)
discard_cp = ofdm.vector_mask_dc_null(block_length, cp_length,
fft_length, dc_null, [])
ofdm_blocks = discard_cp
self.connect(rx_input, serial_to_parallel, discard_cp)
frame_start = [0] * frame_length
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start, True)
print "Disabled time synchronization stage"
print "\t\t\t\t\tframe_length = ", frame_length
if options.ideal is False and options.ideal2 is False:
## Extract preamble, feed to Morelli & Mengali frequency offset estimator
assert (block_header.mm_preamble_pos == 0)
morelli_foe = ofdm.mm_frequency_estimator(fft_length, L, 1, 0)
sampler_preamble = ofdm.vector_sampler(
gr.sizeof_gr_complex * fft_length, 1)
self.connect(ofdm_blocks, (sampler_preamble, 0))
self.connect(frame_start, (sampler_preamble, 1))
self.connect(sampler_preamble, morelli_foe)
freq_offset = morelli_foe
## Adaptive LMS FIR filtering of frequency offset
lms_fir = ofdm.lms_fir_ff(20,
1e-3) # TODO: verify parameter choice
self.connect(freq_offset, lms_fir)
freq_offset = lms_fir
#self.zmq_probe_freqoff = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557")
self.connect(lms_fir, blocks.keep_one_in_n(gr.sizeof_float, 20),
out_disp_cfo)
else:
self.connect(blocks.vector_source_f([1]), out_disp_cfo)
#log_to_file(self, lms_fir, "data/lms_fir.float")
if options.disable_freq_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, freq_offset)
freq_offset = blocks.vector_source_f([0.0], True)
print "Disabled frequency synchronization stage"
if options.ideal is False and options.ideal2 is False:
## Correct frequency shift, feed-forward structure
frequency_shift = ofdm.frequency_shift_vcc(fft_length,
-1.0 / fft_length,
cp_length)
self.connect(ofdm_blocks, (frequency_shift, 0))
self.connect(freq_offset, (frequency_shift, 1))
self.connect(frame_start, (frequency_shift, 2))
ofdm_blocks = frequency_shift
## FFT
fft = fft_blocks.fft_vcc(fft_length, True, [], True)
self.connect(ofdm_blocks, fft)
ofdm_blocks = fft
#log_to_file( self, fft, "data/compen.float" )
## Remove virtual subcarriers
if fft_length > data_subc:
subcarrier_mask = ofdm.vector_mask_dc_null(fft_length,
virtual_subc / 2,
total_subc, dc_null, [])
self.connect(ofdm_blocks, subcarrier_mask)
ofdm_blocks = subcarrier_mask
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
if options.logcir:
log_to_file(self, ofdm_blocks, "data/OFDM_Blocks.compl")
inv_preamble_fd = numpy.array(block_header.pilotsym_fd[
block_header.channel_estimation_pilot[0]])
inv_preamble_fd = numpy.concatenate([
inv_preamble_fd[:total_subc / 2],
inv_preamble_fd[total_subc / 2 + dc_null:]
])
#print "Channel estimation pilot: ", inv_preamble_fd
inv_preamble_fd = 1. / inv_preamble_fd
LS_channel_estimator0 = ofdm.multiply_const_vcc(
list(inv_preamble_fd))
self.connect(ofdm_blocks, LS_channel_estimator0,
gr.null_sink(gr.sizeof_gr_complex * total_subc))
log_to_file(self, LS_channel_estimator0,
"data/OFDM_Blocks_eq.compl")
## post-FFT processing
## extract channel estimation preamble from frame
if options.ideal is False and options.ideal2 is False:
chest_pre_trigger = blocks.delay(gr.sizeof_char, 1)
sampled_chest_preamble = ofdm.vector_sampler(
gr.sizeof_gr_complex * total_subc, 1)
self.connect(frame_start, chest_pre_trigger)
self.connect(chest_pre_trigger, (sampled_chest_preamble, 1))
self.connect(ofdm_blocks, (sampled_chest_preamble, 0))
## Least Squares estimator for channel transfer function (CTF)
inv_preamble_fd = numpy.array(block_header.pilotsym_fd[
block_header.channel_estimation_pilot[0]])
inv_preamble_fd = numpy.concatenate([
inv_preamble_fd[:total_subc / 2],
inv_preamble_fd[total_subc / 2 + dc_null:]
])
#print "Channel estimation pilot: ", inv_preamble_fd
inv_preamble_fd = 1. / inv_preamble_fd
LS_channel_estimator = ofdm.multiply_const_vcc(
list(inv_preamble_fd))
self.connect(sampled_chest_preamble, LS_channel_estimator)
estimated_CTF = LS_channel_estimator
if options.logcir:
log_to_file(self, sampled_chest_preamble, "data/PREAM.compl")
if not options.disable_ctf_enhancer:
if options.logcir:
ifft1 = fft_blocks.fft_vcc(total_subc, False, [], True)
self.connect(
estimated_CTF, ifft1,
gr.null_sink(gr.sizeof_gr_complex * total_subc))
summ1 = ofdm.vector_sum_vcc(total_subc)
c2m = gr.complex_to_mag(total_subc)
self.connect(estimated_CTF, summ1,
gr.null_sink(gr.sizeof_gr_complex))
self.connect(estimated_CTF, c2m,
gr.null_sink(gr.sizeof_float * total_subc))
log_to_file(self, ifft1, "data/CIR1.compl")
log_to_file(self, summ1, "data/CTFsumm1.compl")
log_to_file(self, estimated_CTF, "data/CTF1.compl")
log_to_file(self, c2m, "data/CTFmag1.float")
## MSE enhancer
ctf_mse_enhancer = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
self.connect(estimated_CTF, ctf_mse_enhancer)
# log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
#ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
#null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
#ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
#ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
# total_subc, [] )
#self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )
estimated_CTF = ctf_mse_enhancer
print "Disabled CTF MSE enhancer"
if options.logcir:
ifft2 = fft_blocks.fft_vcc(total_subc, False, [], True)
self.connect(estimated_CTF, ifft2,
gr.null_sink(gr.sizeof_gr_complex * total_subc))
summ2 = ofdm.vector_sum_vcc(total_subc)
c2m2 = gr.complex_to_mag(total_subc)
self.connect(estimated_CTF, summ2,
gr.null_sink(gr.sizeof_gr_complex))
self.connect(estimated_CTF, c2m2,
gr.null_sink(gr.sizeof_float * total_subc))
log_to_file(self, ifft2, "data/CIR2.compl")
log_to_file(self, summ2, "data/CTFsumm2.compl")
log_to_file(self, estimated_CTF, "data/CTF2.compl")
log_to_file(self, c2m2, "data/CTFmag2.float")
## Postprocess the CTF estimate
## CTF -> inverse CTF (for equalizer)
## CTF -> norm |.|^2 (for CTF display)
ctf_postprocess = ofdm.postprocess_CTF_estimate(total_subc)
self.connect(estimated_CTF, ctf_postprocess)
inv_estimated_CTF = (ctf_postprocess, 0)
disp_CTF = (ctf_postprocess, 1)
# if options.disable_equalization or options.ideal:
# terminate_stream(self, inv_estimated_CTF)
# inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
# inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
# self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
# #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
# inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
# self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
# print "Disabled equalization stage"
'''
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print"\t\t\t\t\tnondata_blocks=",nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
nondata_blocks, pilot_subcarriers,0 )
self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
self.connect( frame_start, ( phase_tracking, 2 ) ) ##
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
'''
## Channel Equalizer
if options.disable_equalization or options.ideal or options.ideal2:
print "Disabled equalization stage"
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, inv_estimated_CTF)
else:
equalizer = ofdm.channel_equalizer(total_subc)
self.connect(ofdm_blocks, (equalizer, 0))
self.connect(inv_estimated_CTF, (equalizer, 1))
self.connect(frame_start, (equalizer, 2))
ofdm_blocks = equalizer
#log_to_file(self, equalizer,"data/equalizer_siso.compl")
#log_to_file(self, ofdm_blocks, "data/equalizer.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
if options.ideal is False and options.ideal2 is False:
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print "\t\t\t\t\tnondata_blocks=", nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking2 = ofdm.lms_phase_tracking_dc_null(
total_subc, pilot_subc, nondata_blocks, pilot_subcarriers,
dc_null)
self.connect(ofdm_blocks, (phase_tracking2, 0))
self.connect(frame_start, (phase_tracking2, 1)) ##
if options.disable_phase_tracking or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking2
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
## Output connections
self.connect(ofdm_blocks, out_ofdm_blocks)
self.connect(frame_start, out_frame_start)
if options.ideal is False and options.ideal2 is False:
self.connect(disp_CTF, out_disp_ctf)
else:
self.connect(blocks.vector_source_f([1.0] * total_subc),
blocks.stream_to_vector(gr.sizeof_float, total_subc),
out_disp_ctf)
if log:
log_to_file(self, sc_metric, "data/sc_metric.float")
log_to_file(self, gi_metric, "data/gi_metric.float")
log_to_file(self, morelli_foe, "data/morelli_foe.float")
log_to_file(self, lms_fir, "data/lms_fir.float")
log_to_file(self, sampler_preamble, "data/preamble.compl")
log_to_file(self, sync, "data/sync.compl")
log_to_file(self, frequency_shift, "data/frequency_shift.compl")
log_to_file(self, fft, "data/fft.compl")
log_to_file(self, fft, "data/fft.float", mag=True)
if vars().has_key('subcarrier_mask'):
log_to_file(self, subcarrier_mask,
"data/subcarrier_mask.compl")
log_to_file(self, ofdm_blocks, "data/ofdm_blocks_out.compl")
log_to_file(self,
frame_start,
"data/frame_start.float",
char_to_float=True)
log_to_file(self, sampled_chest_preamble,
"data/sampled_chest_preamble.compl")
log_to_file(self, LS_channel_estimator,
"data/ls_channel_estimator.compl")
log_to_file(self,
LS_channel_estimator,
"data/ls_channel_estimator.float",
mag=True)
if "ctf_mse_enhancer" in locals():
log_to_file(self, ctf_mse_enhancer,
"data/ctf_mse_enhancer.compl")
log_to_file(self,
ctf_mse_enhancer,
"data/ctf_mse_enhancer.float",
mag=True)
log_to_file(self, (ctf_postprocess, 0),
"data/inc_estimated_ctf.compl")
log_to_file(self, (ctf_postprocess, 1), "data/disp_ctf.float")
log_to_file(self, equalizer, "data/equalizer.compl")
log_to_file(self, equalizer, "data/equalizer.float", mag=True)
log_to_file(self, phase_tracking, "data/phase_tracking.compl")
def __init__( self, vlen, cp_len ):
gr.hier_block2.__init__( self,
"channel_estimator_003",
gr.io_signature( 1, 1, gr.sizeof_gr_complex * vlen ),
gr.io_signature( 1, 1, gr.sizeof_gr_complex * vlen ) )
self.ch_est = channel_estimator_001( vlen )
self.connect( self, self.ch_est )
cir_len = cp_len + 1
self.cir_len = cir_len
self.vlen = vlen
self.preamble_td = self.ch_est.td
self.preamble_fd = self.ch_est.fd
# CTF -> CIR
self.cir_est = gr.fft_vcc( vlen, False, [], False ) # IFFT
self.connect( self.ch_est, self.cir_est )
# CIR -> energy per sample
self.cir_energy = gr.complex_to_mag_squared( vlen )
self.connect( self.cir_est, self.cir_energy )
# prepare cyclic convolution of CIR vector
self.cyclic_cir = gr.streams_to_vector( gr.sizeof_float * vlen, 2 )
self.connect( self.cir_energy, ( self.cyclic_cir, 0 ) )
self.connect( self.cir_energy, ( self.cyclic_cir, 1 ) )
# Cyclic convolution of CIR vector
# Pad CIR vector: 0 x cp_len, CIR, CIR, 0 x cp_len
self.serial_ccir = gr.vector_to_stream( gr.sizeof_float, vlen * 2 )
self.padded_sccir = gr.stream_mux( gr.sizeof_float,
[ cir_len-1, 2*vlen, cir_len-1 ] )
if cir_len > 1:
self.conv = gr.fir_filter_fff( 1, [ 1 ] * cir_len )
else:
self.conv = gr.kludge_copy( gr.sizeof_float )
self.connect( self.padded_sccir, self.conv )
self.null_source = gr.null_source( gr.sizeof_float )
self.connect( self.cyclic_cir, self.serial_ccir )
self.connect( self.null_source, ( self.padded_sccir, 0 ) )
self.connect( self.serial_ccir, ( self.padded_sccir, 1 ) )
self.connect( self.null_source, ( self.padded_sccir, 2 ) )
# Extract search window
self.search_window = ofdm.vector_sampler( gr.sizeof_float, vlen )
periodic_trigger_seq = [ 0 ] * ( ( vlen + cir_len-1 ) * 2 )
periodic_trigger_seq[ cir_len-1 + cir_len-1 + vlen-1 ] = 1
self.sampler_trigsrc = gr.vector_source_b( periodic_trigger_seq, True )
self.connect( self.conv, self.search_window )
self.connect( self.sampler_trigsrc, ( self.search_window, 1 ) )
# Find point of maximum energy
self.cir_start = gr.argmax_fs( vlen )
self.connect( self.search_window, self.cir_start )
self.connect( ( self.cir_start, 1 ), gr.null_sink( gr.sizeof_short ) )
# Set to zero all samples that do not belong to the CIR
self.filtered_cir = ofdm.interp_cir_set_noncir_to_zero( vlen, cir_len )
#self.filtered_cir = gr.kludge_copy( gr.sizeof_gr_complex * vlen )
self.connect( self.cir_est, self.filtered_cir )
self.connect( self.cir_start, ( self.filtered_cir, 1 ) )
#self.connect( self.cir_start, gr.null_sink( gr.sizeof_short ) )
# CIR -> CTF
self.filtered_ctf = gr.fft_vcc( vlen, True, [], False ) # FFT
self.scaled_fctf = gr.multiply_const_vcc( [1./vlen]*vlen )
self.connect( self.filtered_cir, self.filtered_ctf )
self.connect( self.filtered_ctf, self.scaled_fctf )
# Output connection
self.connect( self.scaled_fctf, self )
def __init__(self, fft_length, block_length, frame_data_part, block_header,
options):
gr.hier_block2.__init__(
self, "ofdm_receiver", gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature2(2, 2, gr.sizeof_gr_complex * fft_length,
gr.sizeof_char))
frame_length = frame_data_part + block_header.no_pilotsyms
cp_length = block_length - fft_length
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self, self.input)
self.blocks_out = (self, 0)
self.frame_trigger_out = (self, 1)
self.snr_out = (self, 2)
if options.log:
log_to_file(self, self.input, "data/receiver_input.compl")
# peak detector: thresholds low, high
#self._pd_thres_lo = 0.09
#self._pd_thres_hi = 0.1
self._pd_thres = 0.2
self._pd_lookahead = fft_length / 2 # empirically chosen
#########################
# coarse timing offset estimator
# self.tm = schmidl.modified_timing_metric(fft_length,[1]*(fft_length))
self.tm = schmidl.recursive_timing_metric(fft_length)
self.connect(self.input, self.tm)
assert (hasattr(block_header, 'sc_preamble_pos'))
assert (block_header.sc_preamble_pos == 0
) # TODO: relax this restriction
if options.filter_timingmetric:
timingmetric_shift = -2 #int(-cp_length * 0.8)
tmfilter = gr.fir_filter_fff(1, [1. / cp_length] * cp_length)
self.connect(self.tm, tmfilter)
self.timing_metric = tmfilter
print "Filtering timing metric, experimental"
else:
self.timing_metric = self.tm
timingmetric_shift = int(-cp_length / 4)
if options.log:
log_to_file(self, self.timing_metric, "data/tm.float")
# peak detection
#threshold = gr.threshold_ff(self._pd_thres_lo,self._pd_thres_hi,0)
#muted_tm = gr.multiply_ff()
peak_detector = peak_detector_02_fb(self._pd_lookahead, self._pd_thres)
#self.connect(self.timing_metric, threshold, (muted_tm,0))
#self.connect(self.timing_metric, (muted_tm,1))
#self.connect(muted_tm, peak_detector)
self.connect(self.timing_metric, peak_detector)
if options.log:
pd_float = gr.char_to_float()
self.connect(peak_detector, pd_float)
log_to_file(self, pd_float, "data/peakdetector.float")
if options.no_timesync:
terminate_stream(self, peak_detector)
trigger = [0] * (frame_length * block_length)
trigger[block_length - 1] = 1
peak_detector = blocks.vector_source_b(trigger, True)
print "Bypassing timing synchronisation"
# TODO: refine detected peaks with 90% average method as proposed
# from Schmidl & Cox:
# Starting from peak, find first points to the left and right whose
# value is less than or equal 90% of the peak value. New trigger point
# is average of both
# Frequency Offset Estimation
# Used: Algorithm as proposed from Morelli & Mengali
# Idea: Use periodic preamble, correlate identical parts, determine
# phase offset. This phase offset is a function of the frequency offset.
assert (hasattr(block_header, 'mm_preamble_pos'))
foe = morelli_foe(fft_length, block_header.mm_periodic_parts)
self.connect(self.input, (foe, 0))
if block_header.mm_preamble_pos > 0:
delayed_trigger = gr.delay(
gr.sizeof_char, block_header.mm_preamble_pos * block_length)
self.connect(peak_detector, delayed_trigger, (foe, 1))
else:
self.connect(peak_detector, (foe, 1))
self.freq_offset = foe
if options.log:
log_to_file(self, self.freq_offset, "data/freqoff_out.float")
if options.average_freqoff:
#avg_foe = gr.single_pole_iir_filter_ff( 0.1 )
avg_foe = ofdm.lms_fir_ff(20, 1e-3)
self.connect(self.freq_offset, avg_foe)
self.freq_offset = avg_foe
#log_to_file( self, avg_foe, "data/freqoff_out_avg.float" )
print "EXPERIMENTAL!!! Filtering frequency offset estimate"
if options.no_freqsync:
terminate_stream(self, self.freq_offset)
self.freq_offset = blocks.vector_source_f([0.0], True)
print "Bypassing frequency offset estimator, offset=0.0"
# TODO: dynamic solution
frametrig_seq = concatenate([[1], [0] * (frame_length - 1)])
self.time_sync = peak_detector
self.frame_trigger = blocks.vector_source_b(frametrig_seq, True)
self.connect(self.frame_trigger, self.frame_trigger_out)
##########################
# symbol extraction and processing
# First, we extract the whole ofdm block, then we divide this block into
# several ofdm symbols. This asserts that all symbols belonging to the
# same ofdm block will be a consecutive order.
# extract ofdm symbols
# compensate frequency offset
# TODO: use PLL and update/reset signals
delayed_timesync = gr.delay(gr.sizeof_char,
(frame_length - 1) * block_length +
timingmetric_shift)
self.connect(self.time_sync, delayed_timesync)
self.block_sampler = vector_sampler(gr.sizeof_gr_complex,
block_length * frame_length)
self.discard_cp = vector_mask(block_length, cp_length, fft_length, [])
if options.use_dpll:
dpll = gr.dpll_bb(frame_length * block_length, .01)
self.connect(delayed_timesync, dpll)
if options.log:
dpll_f = gr.char_to_float()
delayed_timesync_f = gr.char_to_float()
self.connect(dpll, dpll_f)
self.connect(delayed_timesync, delayed_timesync_f)
log_to_file(self, dpll_f, "data/dpll.float")
log_to_file(self, delayed_timesync_f, "data/dpll_in.float")
delayed_timesync = dpll
print "Using DPLL, EXPERIMENTAL!!!!!"
self.connect(self.input, self.block_sampler)
self.connect(delayed_timesync, (self.block_sampler, 1))
if options.log:
log_to_file(self, self.block_sampler,
"data/block_sampler_out.compl")
# TODO: dynamic solution
self.ofdm_symbols = blocks.vector_to_stream(
gr.sizeof_gr_complex * block_length, frame_length)
self.connect(self.block_sampler, self.ofdm_symbols, self.discard_cp)
if options.log:
log_to_file(self, self.discard_cp, "data/discard_cp_out.compl")
dcp_fft = gr.fft_vcc(fft_length, True, [], True)
self.connect(self.discard_cp, dcp_fft)
log_to_file(self, dcp_fft, "data/discard_cp_fft.compl")
# reset phase accumulator inside freq_shift on every block start
# setup output connection
freq_shift = frequency_shift_vcc(fft_length, -1.0 / fft_length,
cp_length)
self.connect(self.discard_cp, (freq_shift, 0))
self.connect(self.freq_offset, (freq_shift, 1))
self.connect(self.frame_trigger, (freq_shift, 2))
self.connect(freq_shift, self.blocks_out)
if options.log:
log_to_file(self, freq_shift, "data/freqshift_out.compl")
if options.no_freqshift:
terminate_stream(self, freq_shift)
freq_shift = self.discard_cp
print "Bypassing frequency shift block"
def publish_rx_performance_measure(self):
if self._rx_performance_measure_initialized():
return
self.rx_performance_measure_initialized = True
config = station_configuration()
vlen = config.data_subcarriers
vlen_sinr_sc = config.subcarriers
if self.ideal2 is False:
self.setup_ber_measurement()
self.setup_snr_measurement()
ber_mst = self._ber_measuring_tool
if self._options.sinr_est:
sinr_mst = self._sinr_measurement
else:
if self.ideal2 is False:
snr_mst = self._snr_measurement
if self.ideal is False and self.ideal2 is False:
self.ctf = self.filter_ctf()
self.zmq_probe_ctf = zeromq.pub_sink(gr.sizeof_float,config.data_subcarriers, "tcp://*:5559")
self.connect(self.ctf, blocks.keep_one_in_n(gr.sizeof_float*config.data_subcarriers,20) ,self.zmq_probe_ctf)
else:
#self.zmq_probe_ctf = zeromq.pub_sink(gr.sizeof_float,config.subcarriers, "tcp://*:5559")
self.connect(self.ctf,blocks.null_sink(gr.sizeof_float*config.subcarriers))
#self.rx_per_sink = rpsink = corba_rxinfo_sink("himalaya",config.ns_ip,
# config.ns_port,vlen,config.rx_station_id)
# print "BER img xfer"
# self.connect(ber_mst,(rpsink,3))
# ## no sampling needed
# 3. SNR
if self.ideal2 is False:
print "Normal BER measurement"
trig_src = dynamic_trigger_ib(False)
self.connect(self.bitcount_src,trig_src)
ber_sampler = vector_sampler(gr.sizeof_float,1)
self.connect(ber_mst,(ber_sampler,0))
self.connect(trig_src,(ber_sampler,1))
else:
if(self._options.coding):
demod = self._data_decoder
else:
demod = self._data_demodulator
self.connect(self.bitcount_src,blocks.null_sink(gr.sizeof_int) )
self.connect(demod,blocks.null_sink(gr.sizeof_char))
if self._options.log:
trig_src_float = gr.char_to_float()
self.connect(trig_src,trig_src_float)
log_to_file(self, trig_src_float , 'data/dynamic_trigger_out.float')
if self._options.sinr_est is False and self.ideal2 is False:
self.zmq_probe_ber = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5556")
self.connect(ber_sampler,blocks.keep_one_in_n(gr.sizeof_float,20) ,self.zmq_probe_ber)
if self.ideal2 is False:
self.zmq_probe_snr = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5555")
self.connect(snr_mst,blocks.keep_one_in_n(gr.sizeof_float,20) ,self.zmq_probe_snr)
def __init__( self, options, log = False ):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
L = block_header.mm_periodic_parts
frame_data_blocks = options.data_blocks
## Set Input/Output signature
gr.hier_block2.__init__( self,
"ofdm_inner_receiver",
gr.io_signature(
1, 1,
gr.sizeof_gr_complex ),
gr.io_signature4(
4, 4,
gr.sizeof_gr_complex * total_subc, # OFDM blocks
gr.sizeof_char, # Frame start
gr.sizeof_float * total_subc, # Normalized |CTF|^2
gr.sizeof_float * total_subc ) ) # Normalized |CTF|^2
## Input and output ports
self.input = rx_input = (self,0)
out_ofdm_blocks = ( self, 0 )
out_frame_start = ( self, 1 )
out_disp_ctf = ( self, 2 )
out_disp_ctf2 = ( self, 3 )
## pre-FFT processing
## Compute autocorrelations for S&C preamble
## and cyclic prefix
sc_metric = autocorrelator( fft_length/2, fft_length/2 )
gi_metric = autocorrelator( fft_length, cp_length )
self.connect( rx_input, sc_metric )
self.connect( rx_input, gi_metric )
## Sync. Output contains OFDM blocks
sync = ofdm.time_sync( fft_length, cp_length )
self.connect( rx_input, ( sync, 0 ) )
self.connect( sc_metric, ( sync, 1 ) )
self.connect( gi_metric, ( sync, 2 ) )
ofdm_blocks = ( sync, 0 )
frame_start = ( sync, 1 )
if options.disable_time_sync or options.ideal:
terminate_stream(self, ofdm_blocks)
terminate_stream(self, frame_start)
serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
ofdm_blocks = discard_cp
self.connect( rx_input, serial_to_parallel, discard_cp )
frame_start = [0]*frame_length
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start,True)
print "Disabled time synchronization stage"
## Extract preamble, feed to Morelli & Mengali frequency offset estimator
assert( block_header.mm_preamble_pos == 0 )
morelli_foe = ofdm.mm_frequency_estimator( fft_length, L )
sampler_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length,
1 )
self.connect( ofdm_blocks, ( sampler_preamble, 0 ) )
self.connect( frame_start, ( sampler_preamble, 1 ) )
self.connect( sampler_preamble, morelli_foe )
freq_offset = morelli_foe
## Adaptive LMS FIR filtering of frequency offset
lms_fir = ofdm.lms_fir_ff( 20, 1e-3 ) # TODO: verify parameter choice
self.connect( freq_offset, lms_fir )
freq_offset = lms_fir
log_to_file(self, lms_fir, "data/foe_21.float")
# log_to_file(self, lms_fir, "data/lms_fir.float")
# log_to_file(self, lms_fir2, "data/lms_fir2.float")
if options.disable_freq_sync or options.ideal:
terminate_stream(self, freq_offset)
freq_offset = blocks.vector_source_f([0.0],True)
print "Disabled frequency synchronization stage"
## Correct frequency shift, feed-forward structure
frequency_shift = ofdm.frequency_shift_vcc( fft_length, -1.0/fft_length,
cp_length )
self.connect( ofdm_blocks, ( frequency_shift, 0 ) )
self.connect( freq_offset, ( frequency_shift, 1 ) )
self.connect( frame_start, ( frequency_shift, 2 ) )
ofdm_blocks = frequency_shift
## FFT
fft = fft_blocks.fft_vcc( fft_length, True, [], True )
self.connect( ofdm_blocks, fft )
ofdm_blocks = fft
## Remove virtual subcarriers
if fft_length > data_subc:
subcarrier_mask = ofdm.vector_mask( fft_length, virtual_subc/2,
total_subc, [] )
self.connect( ofdm_blocks, subcarrier_mask )
ofdm_blocks = subcarrier_mask
## Least Squares estimator for channel transfer function (CTF)
# if options.logcir:
# log_to_file( self, ofdm_blocks, "data/OFDM_Blocks.compl" )
# inv_preamble_fd = numpy.array( block_header.pilotsym_fd[
# block_header.channel_estimation_pilot[0] ] )
# print "Channel estimation pilot: ", inv_preamble_fd
# inv_preamble_fd = 1. / inv_preamble_fd
# LS_channel_estimator0 = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
# self.connect( ofdm_blocks, LS_channel_estimator0, blocks.null_sink(gr.sizeof_gr_complex*total_subc))
# log_to_file( self, LS_channel_estimator0, "data/OFDM_Blocks_eq.compl" )
## post-FFT processing
## extract channel estimation preamble from frame
if options.est_preamble==1:
chest_pre_trigger = blocks.delay( gr.sizeof_char,
1 )
sampled_chest_preamble = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
self.connect( frame_start, chest_pre_trigger )
self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
self.connect( ofdm_blocks, ( sampled_chest_preamble, 0 ) )
## Least Squares estimator for channel transfer function (CTF)
# Taking inverse for estimating h11 (h12)
inv_preamble_fd_1 = numpy.array( block_header.pilotsym_fd_1[
block_header.channel_estimation_pilot[0] ] )
print "inv_preamble_fd_1: ",inv_preamble_fd_1
inv_preamble_fd_1 = inv_preamble_fd_1[0::2]
#print "inv_preamble_fd_1 ", inv_preamble_fd_1
# Taking inverse for estimating h21 (h22)
inv_preamble_fd_2 = numpy.array( block_header.pilotsym_fd_2[
block_header.channel_estimation_pilot[0] ] )
print "inv_preamble_fd_2: ",inv_preamble_fd_2
inv_preamble_fd_2 = inv_preamble_fd_2[1::2]
#print "inv_preamble_fd_2 ", inv_preamble_fd_2
print "inv_preamble_fd_1: ",inv_preamble_fd_1
print "inv_preamble_fd_2: ",inv_preamble_fd_2
inv_preamble_fd_1 = 1. / inv_preamble_fd_1
inv_preamble_fd_2 = 1. / inv_preamble_fd_2
dd = []
for i in range (total_subc/2):
dd.extend([i*2])
skip_block_1 = ofdm.int_skip(total_subc,2,0)
skip_block_2 = ofdm.int_skip(total_subc,2,1)
# inta_estim_1 = ofdm.interpolator(total_subc,2,dd)
# inta_estim_2 = ofdm.interpolator(total_subc,2,dd)
LS_channel_estimator_1 = ofdm.multiply_const_vcc( list( inv_preamble_fd_1 ) )
LS_channel_estimator_2 = ofdm.multiply_const_vcc( list( inv_preamble_fd_2 ) )
self.connect( sampled_chest_preamble,skip_block_1, LS_channel_estimator_1)#,inta_estim_1 )
self.connect( sampled_chest_preamble,skip_block_2, LS_channel_estimator_2)#,inta_estim_2 )
estimated_CTF_1 = LS_channel_estimator_1 # h0
estimated_CTF_2 = LS_channel_estimator_2 # h1 # h3
if not options.disable_ctf_enhancer:
# if options.logcir:
# ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
# self.connect( estimated_CTF, ifft1,blocks.null_sink(gr.sizeof_gr_complex*total_subc))
# summ1 = ofdm.vector_sum_vcc(total_subc)
# c2m =gr.complex_to_mag(total_subc)
# self.connect( estimated_CTF,summ1 ,blocks.null_sink(gr.sizeof_gr_complex))
# self.connect( estimated_CTF, c2m,blocks.null_sink(gr.sizeof_float*total_subc))
# log_to_file( self, ifft1, "data/CIR1.compl" )
# log_to_file( self, summ1, "data/CTFsumm1.compl" )
# log_to_file( self, estimated_CTF, "data/CTF1.compl" )
# log_to_file( self, c2m, "data/CTFmag1.float" )
## MSE enhancer
ctf_mse_enhancer_1 = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
ctf_mse_enhancer_2 = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
self.connect( estimated_CTF_1, ctf_mse_enhancer_1 )
self.connect( estimated_CTF_2, ctf_mse_enhancer_2 )
estimated_CTF_1 = ctf_mse_enhancer_1
estimated_CTF_2 = ctf_mse_enhancer_2
print "Disabled CTF MSE enhancer"
ctf_postprocess_1 = ofdm.postprocess_CTF_estimate( total_subc/2 )
self.connect( estimated_CTF_1, ( ctf_postprocess_1, 0 ) )
ctf_postprocess_2 = ofdm.postprocess_CTF_estimate( total_subc/2 )
self.connect( estimated_CTF_2, ( ctf_postprocess_2, 0 ) )
inv_CTF_1 = ( ctf_postprocess_1, 0 )
disp_CTF_1 = ( ctf_postprocess_1, 1 )
inv_CTF_2 = ( ctf_postprocess_2, 0 )
disp_CTF_2 = ( ctf_postprocess_2, 1 )
disp_CTF_RX0 = blocks.add_ff(total_subc/2)
self.connect ( disp_CTF_1, (disp_CTF_RX0, 0) )
self.connect ( disp_CTF_2, (disp_CTF_RX0, 1) )
terminate_stream(self,disp_CTF_RX0)
terminate_stream(self,inv_CTF_2)
disp_CTF_RX0 = blocks.null_source(gr.sizeof_float*total_subc)
disp_CTF_RX1 = blocks.null_source(gr.sizeof_float*total_subc)
## Channel Equalizer
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
#log_to_file(self, ofdm_blocks2, "data/vec_mask2.compl")
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
nondata_blocks,pilot_subcarriers,0 )
##phase_tracking = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
## nondata_blocks )
##phase_tracking2 = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
## nondata_blocks )
# self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
# self.connect( ofdm_blocks2, ( phase_tracking, 1 ))
# self.connect( inv_CTF_1, ( phase_tracking, 2 ) )
# self.connect( inv_CTF_3, ( phase_tracking, 3 ) )
# self.connect( frame_start, ( phase_tracking, 4 ) )
# self.connect( frame_start2, ( phase_tracking, 5) )
#
# self.connect( ofdm_blocks2, ( phase_tracking2, 0 ) )
# self.connect( ofdm_blocks, ( phase_tracking2, 1 ))
# self.connect( inv_CTF_3, ( phase_tracking2, 2 ) )
# self.connect( inv_CTF_1, ( phase_tracking2, 3 ) )
# self.connect( frame_start2, ( phase_tracking2, 4 ) )
# self.connect( frame_start, ( phase_tracking2, 5 ) )
self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
self.connect( inv_CTF_1, ( phase_tracking, 1 ) )
self.connect( frame_start, ( phase_tracking, 2 ) )
#self.connect(phase_tracking,blocks.null_sink(gr.sizeof_gr_complex*total_subc))
ofdm_blocks = phase_tracking
'''equalizer = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( ofdm_blocks2, ( equalizer, 1 ) )
self.connect( inv_CTF_1, ( equalizer, 2 ) )
self.connect( inv_CTF_2, ( equalizer, 3 ) )
self.connect( inv_CTF_3, ( equalizer, 4 ) )
self.connect( inv_CTF_4, ( equalizer, 5 ) )
self.connect( frame_start, ( equalizer, 6 ) )
self.connect( frame_start2, ( equalizer, 7 ) )
ofdm_blocks = equalizer'''
equalizer = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( estimated_CTF_1, ( equalizer, 1 ) )
self.connect( estimated_CTF_2, ( equalizer, 2 ) )
self.connect( frame_start, ( equalizer, 3 ) )
#ofdm_blocks = equalizer
#ofdm_blocks2 = equalizer2
ofdm_blocks = equalizer
#log_to_file(self, equalizer,"data/equalizer.compl")
log_to_file(self, ofdm_blocks,"data/equalizer.compl")
log_to_file(self, estimated_CTF_1,"data/estimated_CTF_1.compl")
log_to_file(self, estimated_CTF_2,"data/estimated_CTF_2.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
'''
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
phase_tracking = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer, ( phase_tracking, 0 ) )
self.connect( frame_start, ( phase_tracking, 1 ) )
phase_tracking2 = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer2, ( phase_tracking2, 0 ) )
self.connect( frame_start2, ( phase_tracking2, 1 ) )
# if options.scatter_plot_before_phase_tracking:
# self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
ofdm_blocks2 = phase_tracking2
log_to_file(self,phase_tracking, "data/phase_tracking.compl")
'''
'''combine = blocks.add_cc(config.subcarriers)
self.connect(ofdm_blocks, (combine,0))
self.connect(ofdm_blocks2, (combine,1))
ofdm_blocks = combine'''
## div = gr.multiply_cc(config.subcarriers)
## const = blocks.vector_source_c([[0.5+0]*config.subcarriers],True)
## self.connect(ofdm_blocks,div)
## self.connect(const,(div,1))
## ofdm_blocks=div
# log_to_file(self,combine,"data/combine.compl")
## Output connections
self.connect( ofdm_blocks, out_ofdm_blocks )
self.connect( frame_start, out_frame_start )
self.connect( disp_CTF_RX0, out_disp_ctf )
self.connect( disp_CTF_RX1, out_disp_ctf2 )
else: # (2 preambles for channel estimation)
chest_pre_trigger_1 = blocks.delay( gr.sizeof_char,
1 )
chest_pre_trigger_2 = blocks.delay( gr.sizeof_char,
2 )
sampled_chest_preamble_1 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
sampled_chest_preamble_2 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
self.connect( frame_start, chest_pre_trigger_1 )
self.connect( chest_pre_trigger_1, ( sampled_chest_preamble_1, 1 ) )
self.connect( ofdm_blocks, ( sampled_chest_preamble_1, 0 ) )
self.connect( frame_start, chest_pre_trigger_2 )
self.connect( chest_pre_trigger_2, ( sampled_chest_preamble_2, 1 ) )
self.connect( ofdm_blocks, ( sampled_chest_preamble_2, 0 ) )
## Least Squares estimator for channel transfer function (CTF)
# Taking inverse for estimating h11 (h12)
inv_preamble_fd_1 = numpy.array( block_header.pilotsym_fd_1[
block_header.channel_estimation_pilot[0] ] )
print "inv_preamble_fd_1: ",inv_preamble_fd_1
#inv_preamble_fd_1 = inv_preamble_fd_1[0::2]
#print "inv_preamble_fd_1 ", inv_preamble_fd_1
# Taking inverse for estimating h21 (h22)
inv_preamble_fd_2 = numpy.array( block_header.pilotsym_fd_2[
block_header.channel_estimation_pilot[0]+1 ] )
print "inv_preamble_fd_2: ",inv_preamble_fd_2
#inv_preamble_fd_2 = inv_preamble_fd_2[1::2]
#print "inv_preamble_fd_2 ", inv_preamble_fd_2
print "inv_preamble_fd_1: ",inv_preamble_fd_1
print "inv_preamble_fd_2: ",inv_preamble_fd_2
inv_preamble_fd_1 = 1. / inv_preamble_fd_1
inv_preamble_fd_2 = 1. / inv_preamble_fd_2
#dd = []
#for i in range (total_subc/2):
# dd.extend([i*2])
skip_block_1 = ofdm.int_skip(total_subc,2,0)
skip_block_11 = ofdm.int_skip(total_subc,2,0)
skip_block_2 = ofdm.int_skip(total_subc,2,1)
# inta_estim_1 = ofdm.interpolator(total_subc,2,dd)
# inta_estim_2 = ofdm.interpolator(total_subc,2,dd)
LS_channel_estimator_1 = ofdm.multiply_const_vcc( list( inv_preamble_fd_1 ) )
LS_channel_estimator_2 = ofdm.multiply_const_vcc( list( inv_preamble_fd_2 ) )
self.connect( sampled_chest_preamble_1, LS_channel_estimator_1)#,inta_estim_1 )
self.connect( sampled_chest_preamble_2, LS_channel_estimator_2)#,inta_estim_2 )
estimated_CTF_1 = LS_channel_estimator_1 # h0
estimated_CTF_2 = LS_channel_estimator_2 # h1 # h3
if not options.disable_ctf_enhancer:
# if options.logcir:
# ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
# self.connect( estimated_CTF, ifft1,blocks.null_sink(gr.sizeof_gr_complex*total_subc))
# summ1 = ofdm.vector_sum_vcc(total_subc)
# c2m =gr.complex_to_mag(total_subc)
# self.connect( estimated_CTF,summ1 ,blocks.null_sink(gr.sizeof_gr_complex))
# self.connect( estimated_CTF, c2m,blocks.null_sink(gr.sizeof_float*total_subc))
# log_to_file( self, ifft1, "data/CIR1.compl" )
# log_to_file( self, summ1, "data/CTFsumm1.compl" )
# log_to_file( self, estimated_CTF, "data/CTF1.compl" )
# log_to_file( self, c2m, "data/CTFmag1.float" )
## MSE enhancer
ctf_mse_enhancer_1 = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
ctf_mse_enhancer_2 = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
self.connect( estimated_CTF_1, ctf_mse_enhancer_1 )
self.connect( estimated_CTF_2, ctf_mse_enhancer_2 )
estimated_CTF_1 = ctf_mse_enhancer_1
estimated_CTF_2 = ctf_mse_enhancer_2
print "Disabled CTF MSE enhancer"
ctf_postprocess_1 = ofdm.postprocess_CTF_estimate( total_subc )
self.connect( estimated_CTF_1, ( ctf_postprocess_1, 0 ) )
ctf_postprocess_2 = ofdm.postprocess_CTF_estimate( total_subc )
self.connect( estimated_CTF_2, ( ctf_postprocess_2, 0 ) )
inv_CTF_1 = ( ctf_postprocess_1, 0 )
disp_CTF_1 = ( ctf_postprocess_1, 1 )
inv_CTF_2 = ( ctf_postprocess_2, 0 )
disp_CTF_2 = ( ctf_postprocess_2, 1 )
#disp_CTF_RX0 = blocks.add_ff(total_subc)
#self.connect ( disp_CTF_1, (disp_CTF_RX0, 0) )
#self.connect ( disp_CTF_2, (disp_CTF_RX0, 1) )
#terminate_stream(self,disp_CTF_RX0)
terminate_stream(self,inv_CTF_2)
disp_CTF_RX0 = disp_CTF_1
disp_CTF_RX1 = disp_CTF_2
## Channel Equalizer
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
#log_to_file(self, ofdm_blocks2, "data/vec_mask2.compl")
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
nondata_blocks,pilot_subcarriers,0 )
##phase_tracking = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
## nondata_blocks )
##phase_tracking2 = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
## nondata_blocks )
# self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
# self.connect( ofdm_blocks2, ( phase_tracking, 1 ))
# self.connect( inv_CTF_1, ( phase_tracking, 2 ) )
# self.connect( inv_CTF_3, ( phase_tracking, 3 ) )
# self.connect( frame_start, ( phase_tracking, 4 ) )
# self.connect( frame_start2, ( phase_tracking, 5) )
#
# self.connect( ofdm_blocks2, ( phase_tracking2, 0 ) )
# self.connect( ofdm_blocks, ( phase_tracking2, 1 ))
# self.connect( inv_CTF_3, ( phase_tracking2, 2 ) )
# self.connect( inv_CTF_1, ( phase_tracking2, 3 ) )
# self.connect( frame_start2, ( phase_tracking2, 4 ) )
# self.connect( frame_start, ( phase_tracking2, 5 ) )
self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
self.connect( inv_CTF_1, skip_block_11, ( phase_tracking, 1 ) )
self.connect( frame_start, ( phase_tracking, 2 ) )
#self.connect(phase_tracking,blocks.null_sink(gr.sizeof_gr_complex*total_subc))
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
'''equalizer = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( ofdm_blocks2, ( equalizer, 1 ) )
self.connect( inv_CTF_1, ( equalizer, 2 ) )
self.connect( inv_CTF_2, ( equalizer, 3 ) )
self.connect( inv_CTF_3, ( equalizer, 4 ) )
self.connect( inv_CTF_4, ( equalizer, 5 ) )
self.connect( frame_start, ( equalizer, 6 ) )
self.connect( frame_start2, ( equalizer, 7 ) )
ofdm_blocks = equalizer'''
equalizer = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( estimated_CTF_1, skip_block_1, ( equalizer, 1 ) )
self.connect( estimated_CTF_2, skip_block_2, ( equalizer, 2 ) )
self.connect( frame_start, ( equalizer, 3 ) )
#ofdm_blocks = equalizer
#ofdm_blocks2 = equalizer2
ofdm_blocks = equalizer
#log_to_file(self, equalizer,"data/equalizer.compl")
log_to_file(self, ofdm_blocks,"data/equalizer.compl")
log_to_file(self, estimated_CTF_1,"data/estimated_CTF_1.compl")
log_to_file(self, estimated_CTF_2,"data/estimated_CTF_2.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
'''
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
phase_tracking = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer, ( phase_tracking, 0 ) )
self.connect( frame_start, ( phase_tracking, 1 ) )
phase_tracking2 = ofdm.lms_phase_tracking_02( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer2, ( phase_tracking2, 0 ) )
self.connect( frame_start2, ( phase_tracking2, 1 ) )
# if options.scatter_plot_before_phase_tracking:
# self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
ofdm_blocks2 = phase_tracking2
log_to_file(self,phase_tracking, "data/phase_tracking.compl")
'''
'''combine = blocks.add_cc(config.subcarriers)
self.connect(ofdm_blocks, (combine,0))
self.connect(ofdm_blocks2, (combine,1))
ofdm_blocks = combine'''
## div = gr.multiply_cc(config.subcarriers)
## const = blocks.vector_source_c([[0.5+0]*config.subcarriers],True)
## self.connect(ofdm_blocks,div)
## self.connect(const,(div,1))
## ofdm_blocks=div
# log_to_file(self,combine,"data/combine.compl")
## Output connections
self.connect( ofdm_blocks, out_ofdm_blocks )
self.connect( frame_start, out_frame_start )
self.connect( disp_CTF_RX0, out_disp_ctf )
self.connect( disp_CTF_RX1, out_disp_ctf2 )
def __init__( self, options, log = False ):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
#cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
L = block_header.mm_periodic_parts
cp_length = config.cp_length
print "data_subc: ", config.data_subcarriers
print "total_subc: ", config.subcarriers
print "frame_lengthframe_length: ", frame_length
## Set Input/Output signature
gr.hier_block2.__init__( self,
"fbmc_inner_receiver",
gr.io_signature(
1, 1,
gr.sizeof_gr_complex ),
gr.io_signaturev(
4, 4,
[gr.sizeof_float * total_subc, # Normalized |CTF|^2
gr.sizeof_char, # Frame start
gr.sizeof_gr_complex * total_subc, # OFDM blocks, SNR est
gr.sizeof_float] ) ) # CFO
## Input and output ports
self.input = rx_input = self
out_ofdm_blocks = ( self, 2 )
out_frame_start = ( self, 1 )
out_disp_ctf = ( self, 0 )
out_disp_cfo = ( self, 3 )
#out_snr_pream = ( self, 3 )
## pre-FFT processing
'''
## Compute autocorrelations for S&C preamble
## and cyclic prefix
self._sc_metric = sc_metric = autocorrelator( fft_length/2, fft_length/2 )
self._gi_metric = gi_metric = autocorrelator( fft_length, cp_length )
self.connect( rx_input, sc_metric )
self.connect( rx_input, gi_metric )
terminate_stream(self, gi_metric)
## Sync. Output contains OFDM blocks
sync = ofdm.time_sync( fft_length/2, 1)
self.connect( rx_input, ( sync, 0 ) )
self.connect( sc_metric, ( sync, 1 ) )
self.connect( sc_metric, ( sync, 2 ) )
ofdm_blocks = ( sync, 0 )
frame_start = ( sync, 1 )
log_to_file( self, ( sync, 1 ), "data/fbmc_peak_detector.char" )
'''
if options.ideal is False and options.ideal2 is False:
#Testing old/new metric
self.tm = schmidl.recursive_timing_metric(2*fft_length)
self.connect( self.input, self.tm)
#log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm.float" )
timingmetric_shift = 0 #-2 #int(-cp_length * 0.8)
tmfilter = filter.fft_filter_fff(1, [2./fft_length]*(fft_length/2))# ofdm.lms_fir_ff( fft_length, 1e-3 ) #; filter.fir_filter_fff(1, [1./fft_length]*fft_length)
self.connect( self.tm, tmfilter )
self.tm = tmfilter
#log_to_file( self, self.tm, "data/fbmc_rec_sc_metric_ofdm2.float" )
self._pd_thres = 0.6
self._pd_lookahead = fft_length # empirically chosen
peak_detector = ofdm.peak_detector_02_fb(self._pd_lookahead, self._pd_thres)
self.connect(self.tm, peak_detector)
#log_to_file( self, peak_detector, "data/fbmc_rec_peak_detector.char" )
#frame_start = [0]*frame_length
#frame_start[0] = 1
#frame_start = blocks.vector_source_b(frame_start,True)
#OLD
#delayed_timesync = blocks.delay(gr.sizeof_char,
# (frame_length-10)*fft_length/2 - fft_length/4 -1 + timingmetric_shift)
delayed_timesync = blocks.delay(gr.sizeof_char,
(frame_length-10)*fft_length/2 - fft_length/4 + int(2.5*fft_length) + timingmetric_shift-1)
#delayed_timesync = blocks.delay(gr.sizeof_char,
#(frame_length-10)*fft_length/2 - fft_length/4 + int(3.5*fft_length) + timingmetric_shift-1)
self.connect( peak_detector, delayed_timesync )
self.block_sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,fft_length/2*frame_length)
self.connect(self.input,self.block_sampler)
self.connect(delayed_timesync,(self.block_sampler,1))
#log_to_file( self, self.block_sampler, "data/fbmc_block_sampler.compl" )
vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*fft_length,
frame_length/2)
self.connect(self.block_sampler,vt2s)
#terminate_stream(self,ofdm_blocks)
ofdm_blocks = vt2s
'''
# TODO: dynamic solution
vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length/2,
frame_length)
self.connect(self.block_sampler,vt2s)
terminate_stream(self,( sync, 0 ))
ofdm_blocks = vt2s
'''
##stv_help = blocks.stream_to_vector(gr.sizeof_gr_complex*config.fft_length/2, 1)
#stv_help = blocks.vector_to_stream(gr.sizeof_gr_complex*config.fft_length/2, 2)
##self.connect(ofdm_blocks, stv_help)
##ofdm_blocks = stv_help
#ofdm_blocks = ( sync, 0 )
#frame_start = ( sync, 1 )
#log_to_file(self, frame_start, "data/frame_start.compl")
#log_to_file( self, sc_metric, "data/sc_metric.float" )
#log_to_file( self, gi_metric, "data/gi_metric.float" )
#log_to_file( self, (sync,1), "data/sync.float" )
# log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
frame_start = [0]*int(frame_length/2)
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start,True)
#frame_start2 = [0]*int(frame_length/2)
#frame_start2[0] = 1
#frame_start2 = blocks.vector_source_b(frame_start2,True)
if options.disable_time_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, ofdm_blocks)
terminate_stream(self, frame_start)
serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,fft_length)
#discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
#serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
#discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
#self.connect( rx_input,serial_to_parallel)
#self.connect( rx_input, blocks.delay(gr.sizeof_gr_complex,0),serial_to_parallel)
initial_skip = blocks.skiphead(gr.sizeof_gr_complex,2*fft_length)
self.connect( rx_input, initial_skip)
if options.ideal is False and options.ideal2 is False:
self.connect( initial_skip, serial_to_parallel)
ofdm_blocks = serial_to_parallel
else:
ofdm_blocks = initial_skip
#self.connect( rx_input, serial_to_parallel, discard_cp )
frame_start = [0]*int(frame_length/2)
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start,True)
#frame_start2 = [0]*int(frame_length/2)
#frame_start2[0] = 1
#frame_start2 = blocks.vector_source_b(frame_start2,True)
print "Disabled time synchronization stage"
print"\t\t\t\t\tframe_length = ",frame_length
if options.ideal is False and options.ideal2 is False:
## Extract preamble, feed to Morelli & Mengali frequency offset estimator
assert( block_header.mm_preamble_pos == 0 )
morelli_foe = ofdm.mm_frequency_estimator( fft_length, 2, 1, config.fbmc )
sampler_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length,
1 )
self.connect( ofdm_blocks, ( sampler_preamble, 0 ) )
self.connect( frame_start, blocks.delay( gr.sizeof_char, 1 ), ( sampler_preamble, 1 ) )
self.connect( sampler_preamble, morelli_foe )
freq_offset = morelli_foe
print "FRAME_LENGTH: ", frame_length
#log_to_file( self, sampler_preamble, "data/sampler_preamble.compl" )
#log_to_file( self, rx_input, "data/rx_input.compl" )
#log_to_file( self, ofdm_blocks, "data/rx_input.compl" )
#Extracting preamble for SNR estimation
#fft_snr_est = fft_blocks.fft_vcc( fft_length, True, [], True )
#self.connect( sampler_preamble, blocks.stream_to_vector(gr.sizeof_gr_complex*fft_length/2, 2), fft_snr_est )
## Remove virtual subcarriers
#if fft_length > data_subc:
#subcarrier_mask_snr_est = ofdm.vector_mask( fft_length, virtual_subc/2,
# total_subc, [] )
#self.connect( fft_snr_est, subcarrier_mask_snr_est )
#fft_snr_est = subcarrier_mask_snr_est
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
#self.connect( fft_snr_est, out_snr_pream ) # Connecting to output
## Adaptive LMS FIR filtering of frequency offset
lms_fir = ofdm.lms_fir_ff( 20, 1e-3 ) # TODO: verify parameter choice
self.connect( freq_offset, lms_fir )
freq_offset = lms_fir
self.connect(freq_offset, blocks.keep_one_in_n(gr.sizeof_float,20) ,out_disp_cfo)
else:
self.connect(blocks.vector_source_f ([1]) ,out_disp_cfo)
#log_to_file(self, lms_fir, "data/lms_fir.float")
if options.disable_freq_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, freq_offset)
freq_offset = blocks.vector_source_f([0.0],True)
print "Disabled frequency synchronization stage"
if options.ideal is False and options.ideal2 is False:
## Correct frequency shift, feed-forward structure
frequency_shift = ofdm.frequency_shift_vcc( fft_length, -1.0/fft_length,
0)
#freq_shift = blocks.multiply_cc()
#norm_freq = -0.1 / config.fft_length
#freq_off = self.freq_off_src = analog.sig_source_c(1.0, analog.GR_SIN_WAVE, norm_freq, 1.0, 0.0 )
self.connect( ofdm_blocks, ( frequency_shift, 0 ) )
self.connect( freq_offset, ( frequency_shift, 1 ) )
self.connect( frame_start,blocks.delay( gr.sizeof_char, 0), ( frequency_shift, 2 ) )
#self.connect(frequency_shift,s2help)
#ofdm_blocks = s2help
ofdm_blocks = frequency_shift
#terminate_stream(self, frequency_shift)
#inner_pb_filt = self._inner_pilot_block_filter = fbmc_inner_pilot_block_filter()
#self.connect(ofdm_blocks,inner_pb_filt)
#self.connect(frame_start,(inner_pb_filt,1))
#self.connect((inner_pb_filt,1),blocks.null_sink(gr.sizeof_char))
#ofdm_blocks = (inner_pb_filt,0)
overlap_ser_to_par = ofdm.fbmc_overlapping_serial_to_parallel_cvc(fft_length)
self.separate_vcvc = ofdm.fbmc_separate_vcvc(fft_length, 2)
self.polyphase_network_vcvc_1 = ofdm.fbmc_polyphase_network_vcvc(fft_length, 4, 4*fft_length-1, True)
self.polyphase_network_vcvc_2 = ofdm.fbmc_polyphase_network_vcvc(fft_length, 4, 4*fft_length-1, True)
self.junction_vcvc = ofdm.fbmc_junction_vcvc(fft_length, 2)
self.fft_fbmc = fft_blocks.fft_vcc(fft_length, True, [], True)
print "config.training_data.fbmc_no_preambles: ", config.training_data.fbmc_no_preambles
#center_preamble = [1, -1j, -1, 1j]
#self.preamble = preamble = [0]*total_subc + center_preamble*((int)(total_subc/len(center_preamble)))+[0]*total_subc
self.preamble = preamble = config.training_data.fbmc_pilotsym_fd_list
#inv_preamble = 1. / numpy.array(self.preamble)
#print "self.preamble: ", len(self.preamble
#print "inv_preamble: ", list(inv_preamble)
#print "self.preamble", self.preamble
#print "self.preamble2", self.preamble2
self.multiply_const= ofdm.multiply_const_vcc(([1.0/(math.sqrt(fft_length*0.6863))]*total_subc))
self.beta_multiplier_vcvc = ofdm.fbmc_beta_multiplier_vcvc(total_subc, 4, 4*fft_length-1, 0)
#self.skiphead = blocks.skiphead(gr.sizeof_gr_complex*total_subc, 2*4-1-1)
self.skiphead = blocks.skiphead(gr.sizeof_gr_complex*total_subc,2)
self.skiphead_1 = blocks.skiphead(gr.sizeof_gr_complex*total_subc, 0)
#self.remove_preamble_vcvc = ofdm.fbmc_remove_preamble_vcvc(total_subc, config.frame_data_part/2, config.training_data.fbmc_no_preambles*total_subc/2)
#self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(total_subc, config.frame_data_part, 1, 2, 1, 0)
self.oqam_postprocessing_vcvc = ofdm.fbmc_oqam_postprocessing_vcvc(total_subc, 0, 0)
#log_to_file( self, ofdm_blocks, "data/PRE_FBMC.compl" )
#log_to_file( self, self.fft_fbmc, "data/FFT_FBMC.compl" )
if options.ideal is False and options.ideal2 is False:
self.subchannel_processing_vcvc = ofdm.fbmc_subchannel_processing_vcvc(total_subc, config.frame_data_part, 3, 2, 1, 0)
help2 = blocks.keep_one_in_n(gr.sizeof_gr_complex*total_subc,frame_length)
self.connect ((self.subchannel_processing_vcvc,1),help2)
#log_to_file( self, self.subchannel_processing_vcvc, "data/fbmc_subc.compl" )
#terminate_stream(self, help2)
if options.ideal is False and options.ideal2 is False:
self.connect(ofdm_blocks, blocks.vector_to_stream(gr.sizeof_gr_complex, fft_length),overlap_ser_to_par)
else:
self.connect(ofdm_blocks,overlap_ser_to_par)
self.connect(overlap_ser_to_par, self.separate_vcvc)
self.connect((self.separate_vcvc, 1), (self.polyphase_network_vcvc_2, 0))
self.connect((self.separate_vcvc, 0), (self.polyphase_network_vcvc_1, 0))
self.connect((self.polyphase_network_vcvc_1, 0), (self.junction_vcvc, 0))
self.connect((self.polyphase_network_vcvc_2, 0), (self.junction_vcvc, 1))
self.connect(self.junction_vcvc, self.fft_fbmc)
ofdm_blocks = self.fft_fbmc
print "config.dc_null: ", config.dc_null
if fft_length > data_subc:
subcarrier_mask_fbmc = ofdm.vector_mask_dc_null( fft_length, virtual_subc/2,
total_subc, config.dc_null, [] )
self.connect( ofdm_blocks, subcarrier_mask_fbmc )
ofdm_blocks = subcarrier_mask_fbmc
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
#log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
self.connect(ofdm_blocks, self.beta_multiplier_vcvc)
ofdm_blocks = self.beta_multiplier_vcvc
#self.connect(ofdm_blocks,self.multiply_const)
#self.connect(self.multiply_const, (self.skiphead, 0))
self.connect(ofdm_blocks, (self.skiphead, 0))
#log_to_file( self, self.skiphead, "data/fbmc_skiphead_4.compl" )
#self.connect(ofdm_blocks, self.multiply_const)
#self.connect(self.multiply_const, self.beta_multiplier_vcvc)
#self.connect((self.beta_multiplier_vcvc, 0), (self.skiphead, 0))
if options.ideal or options.ideal2:
self.connect((self.skiphead, 0),(self.skiphead_1, 0))
else:
self.connect((self.skiphead, 0), (self.subchannel_processing_vcvc, 0))
self.connect((self.subchannel_processing_vcvc, 0), (self.skiphead_1, 0))
#log_to_file( self, self.skiphead, "data/fbmc_subc.compl" )
#self.connect((self.skiphead_1, 0),(self.remove_preamble_vcvc, 0))
#self.connect((self.remove_preamble_vcvc, 0), (self.oqam_postprocessing_vcvc, 0))
#ofdm_blocks = self.oqam_postprocessing_vcvc
#log_to_file( self, self.subchannel_processing_vcvc, "data/subc_0.compl" )
#log_to_file( self, (self.subchannel_processing_vcvc,1), "data/subc_1.compl" )
self.connect((self.skiphead_1, 0),(self.oqam_postprocessing_vcvc, 0))
#self.connect((self.oqam_postprocessing_vcvc, 0), (self.remove_preamble_vcvc, 0) )
ofdm_blocks = (self.oqam_postprocessing_vcvc, 0)#(self.remove_preamble_vcvc, 0)
#log_to_file( self, (self.oqam_postprocessing_vcvc, 0), "data/fbmc_before_remove.compl" )
#log_to_file( self, self.skiphead, "data/SKIP_HEAD_FBMC.compl" )
#log_to_file( self, self.beta_multiplier_vcvc, "data/BETA_REC_FBMC.compl" )
#log_to_file( self, self.oqam_postprocessing_vcvc, "data/REC_OUT_FBMC.compl" )
""" DISABLED OFDM CHANNEL ESTIMATION PREMBLE -> CORRECT LATER to compare FBMC and OFDM channel estimation
#TAKING THE CHANNEL ESTIMATION PREAMBLE
chest_pre_trigger = blocks.delay( gr.sizeof_char, 3 )
sampled_chest_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length/2, 2 )
self.connect( frame_start, chest_pre_trigger )
self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
self.connect( frequency_shift, ( sampled_chest_preamble, 0 ) )
#ofdm_blocks = sampled_chest_preamble
## FFT
fft = fft_blocks.fft_vcc( fft_length, True, [], True )
self.connect( sampled_chest_preamble, fft )
ofdm_blocks_est = fft
log_to_file( self, sampled_chest_preamble, "data/SAMPLED_EST_PREAMBLE.compl" )
log_to_file( self, ofdm_blocks_est, "data/FFT.compl" )
## Remove virtual subcarriers
if fft_length > data_subc:
subcarrier_mask = ofdm.vector_mask( fft_length, virtual_subc/2,
total_subc, [] )
self.connect( ofdm_blocks_est, subcarrier_mask )
ofdm_blocks_est = subcarrier_mask
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
log_to_file( self, subcarrier_mask, "data/OFDM_Blocks.compl" )
## post-FFT processing
## extract channel estimation preamble from frame
##chest_pre_trigger = blocks.delay( gr.sizeof_char,
##1 )
##sampled_chest_preamble = \
## ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
##self.connect( frame_start, chest_pre_trigger )
##self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
##self.connect( ofdm_blocks, ( sampled_chest_preamble, 0 ) )
## Least Squares estimator for channel transfer function (CTF)
inv_preamble_fd = numpy.array( block_header.pilotsym_fd[
block_header.channel_estimation_pilot[0] ] )
#print "Channel estimation pilot: ", inv_preamble_fd
inv_preamble_fd = 1. / inv_preamble_fd
LS_channel_estimator = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
self.connect( ofdm_blocks_est, LS_channel_estimator )
estimated_CTF = LS_channel_estimator
terminate_stream(self,estimated_CTF)
"""
if options.ideal is False and options.ideal2 is False:
if options.logcir:
log_to_file( self, sampled_chest_preamble, "data/PREAM.compl" )
if not options.disable_ctf_enhancer:
if options.logcir:
ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
self.connect( estimated_CTF, ifft1,gr.null_sink(gr.sizeof_gr_complex*total_subc))
summ1 = ofdm.vector_sum_vcc(total_subc)
c2m =gr.complex_to_mag(total_subc)
self.connect( estimated_CTF,summ1 ,gr.null_sink(gr.sizeof_gr_complex))
self.connect( estimated_CTF, c2m,gr.null_sink(gr.sizeof_float*total_subc))
log_to_file( self, ifft1, "data/CIR1.compl" )
log_to_file( self, summ1, "data/CTFsumm1.compl" )
log_to_file( self, estimated_CTF, "data/CTF1.compl" )
log_to_file( self, c2m, "data/CTFmag1.float" )
## MSE enhancer
ctf_mse_enhancer = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
self.connect( estimated_CTF, ctf_mse_enhancer )
# log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
#ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
#null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
#ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
#ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
# total_subc, [] )
#self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )
estimated_CTF = ctf_mse_enhancer
print "Disabled CTF MSE enhancer"
if options.logcir:
ifft2 = fft_blocks.fft_vcc(total_subc,False,[],True)
self.connect( estimated_CTF, ifft2,gr.null_sink(gr.sizeof_gr_complex*total_subc))
summ2 = ofdm.vector_sum_vcc(total_subc)
c2m2 =gr.complex_to_mag(total_subc)
self.connect( estimated_CTF,summ2 ,gr.null_sink(gr.sizeof_gr_complex))
self.connect( estimated_CTF, c2m2,gr.null_sink(gr.sizeof_float*total_subc))
log_to_file( self, ifft2, "data/CIR2.compl" )
log_to_file( self, summ2, "data/CTFsumm2.compl" )
log_to_file( self, estimated_CTF, "data/CTF2.compl" )
log_to_file( self, c2m2, "data/CTFmag2.float" )
## Postprocess the CTF estimate
## CTF -> inverse CTF (for equalizer)
## CTF -> norm |.|^2 (for CTF display)
ctf_postprocess = ofdm.fbmc_postprocess_CTF_estimate( total_subc )
self.connect( help2, ctf_postprocess )
#estimated_SNR = ( ctf_postprocess, 0 )
disp_CTF = ( ctf_postprocess, 0 )
#self.connect(estimated_SNR,out_snr_pream)
#log_to_file( self, estimated_SNR, "data/fbmc_SNR.float" )
#Disable measured SNR output
#terminate_stream(self, estimated_SNR)
#self.connect(blocks.vector_source_f([10.0],True) ,out_snr_pream)
# if options.disable_equalization or options.ideal:
# terminate_stream(self, inv_estimated_CTF)
# inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
# inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
# self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
# #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
# inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
# self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
# print "Disabled equalization stage"
'''
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print"\t\t\t\t\tnondata_blocks=",nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
nondata_blocks, pilot_subcarriers,0 )
self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
self.connect( frame_start, ( phase_tracking, 2 ) ) ##
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
'''
## Channel Equalizer
##equalizer = ofdm.channel_equalizer( total_subc )
##self.connect( ofdm_blocks, ( equalizer, 0 ) )
##self.connect( inv_estimated_CTF, ( equalizer, 1 ) )
##self.connect( frame_start, ( equalizer, 2 ) )
##ofdm_blocks = equalizer
#log_to_file(self, equalizer,"data/equalizer_siso.compl")
#log_to_file(self, ofdm_blocks, "data/equalizer.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print"\t\t\t\t\tnondata_blocks=",nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
## Output connections
self.connect( ofdm_blocks, out_ofdm_blocks )
self.connect( frame_start, out_frame_start )
if options.ideal is False and options.ideal2 is False:
self.connect( disp_CTF, out_disp_ctf )
else:
self.connect( blocks.vector_source_f([1.0]*total_subc),blocks.stream_to_vector(gr.sizeof_float,total_subc), out_disp_ctf )
if log:
log_to_file( self, sc_metric, "data/sc_metric.float" )
log_to_file( self, gi_metric, "data/gi_metric.float" )
log_to_file( self, morelli_foe, "data/morelli_foe.float" )
log_to_file( self, lms_fir, "data/lms_fir.float" )
log_to_file( self, sampler_preamble, "data/preamble.compl" )
log_to_file( self, sync, "data/sync.compl" )
log_to_file( self, frequency_shift, "data/frequency_shift.compl" )
log_to_file( self, fft, "data/fft.compl")
log_to_file( self, fft, "data/fft.float", mag=True )
if vars().has_key( 'subcarrier_mask' ):
log_to_file( self, subcarrier_mask, "data/subcarrier_mask.compl" )
log_to_file( self, ofdm_blocks, "data/ofdm_blocks_out.compl" )
log_to_file( self, frame_start, "data/frame_start.float",
char_to_float=True )
log_to_file( self, sampled_chest_preamble,
"data/sampled_chest_preamble.compl" )
log_to_file( self, LS_channel_estimator,
"data/ls_channel_estimator.compl" )
log_to_file( self, LS_channel_estimator,
"data/ls_channel_estimator.float", mag=True )
if "ctf_mse_enhancer" in locals():
log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.compl" )
log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.float",
mag=True )
log_to_file( self, (ctf_postprocess,0), "data/inc_estimated_ctf.compl" )
log_to_file( self, (ctf_postprocess,1), "data/disp_ctf.float" )
log_to_file( self, equalizer, "data/equalizer.compl" )
log_to_file( self, equalizer, "data/equalizer.float", mag=True )
log_to_file( self, phase_tracking, "data/phase_tracking.compl" )
def __init__(self, options):
gr.hier_block2.__init__(self, "fbmc_receive_path",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(0,0,0))
print "This is FBMC receive path 1x1"
common_options.defaults(options)
config = self.config = station_configuration()
config.data_subcarriers = dsubc = options.subcarriers
config.cp_length = 0
config.frame_data_blocks = options.data_blocks
config._verbose = options.verbose #TODO: update
config.fft_length = options.fft_length
config.dc_null = options.dc_null
config.training_data = default_block_header(dsubc,
config.fft_length,config.dc_null,options)
config.coding = options.coding
config.ber_window = options.ber_window
config.periodic_parts = 8
config.frame_id_blocks = 1 # FIXME
self._options = copy.copy(options) #FIXME: do we need this?
config.fbmc = options.fbmc
config.block_length = config.fft_length + config.cp_length
config.frame_data_part = config.frame_data_blocks + config.frame_id_blocks
config.frame_length = config.training_data.fbmc_no_preambles + 2*config.frame_data_part
config.postpro_frame_length = config.frame_data_part + \
config.training_data.no_pilotsyms
config.subcarriers = dsubc + \
config.training_data.pilot_subcarriers
config.virtual_subcarriers = config.fft_length - config.subcarriers - config.dc_null
total_subc = config.subcarriers
# check some bounds
if config.fft_length < config.subcarriers:
raise SystemError, "Subcarrier number must be less than FFT length"
if config.fft_length < config.cp_length:
raise SystemError, "Cyclic prefix length must be less than FFT length"
#self.input = gr.kludge_copy(gr.sizeof_gr_complex)
#self.connect( self, self.input )
self.input = self
self.ideal = options.ideal
self.ideal2 = options.ideal2
## Inner receiver
## Timing & Frequency Synchronization
## Channel estimation + Equalization
## Phase Tracking for sampling clock frequency offset correction
inner_receiver = self.inner_receiver = fbmc_inner_receiver( options, options.log )
self.connect( self.input, inner_receiver )
ofdm_blocks = ( inner_receiver, 2 )
frame_start = ( inner_receiver, 1 )
disp_ctf = ( inner_receiver, 0 )
#self.snr_est_preamble = ( inner_receiver, 3 )
#terminate_stream(self,snr_est_preamble)
disp_cfo = ( inner_receiver, 3 )
if self.ideal is False and self.ideal2 is False:
self.zmq_probe_freqoff = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557")
self.connect(disp_cfo, self.zmq_probe_freqoff)
else:
self.connect(disp_cfo, blocks.null_sink(gr.sizeof_float))
# for ID decoder
used_id_bits = config.used_id_bits = 8 #TODO: constant in source code!
rep_id_bits = config.rep_id_bits = dsubc/used_id_bits #BPSK
if options.log:
print "rep_id_bits %d" % (rep_id_bits)
if dsubc % used_id_bits <> 0:
raise SystemError,"Data subcarriers need to be multiple of 10"
## Workaround to avoid periodic structure
seed(1)
whitener_pn = [randint(0,1) for i in range(used_id_bits*rep_id_bits)]
## NOTE!!! BIG HACK!!!
## first preamble ain't equalized ....
## for Milan's SNR estimator
## Outer Receiver
## Make new inner receiver compatible with old outer receiver
## FIXME: renew outer receiver
self.ctf = disp_ctf
#frame_sampler = ofdm_frame_sampler(options)
frame_sampler = fbmc_frame_sampler(options)
self.connect( ofdm_blocks, frame_sampler)
self.connect( frame_start, (frame_sampler,1) )
#
# ft = [0] * config.frame_length
# ft[0] = 1
#
# # The next block ensures that only complete frames find their way into
# # the old outer receiver. The dynamic frame start trigger is hence
# # replaced with a static one, fixed to the frame length.
#
# frame_sampler = ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc,
# config.frame_length )
# self.symbol_output = blocks.vector_to_stream( gr.sizeof_gr_complex * total_subc,
# config.frame_length )
# delayed_frame_start = blocks.delay( gr.sizeof_char, config.frame_length - 1 )
# damn_static_frame_trigger = blocks.vector_source_b( ft, True )
#
# if options.enable_erasure_decision:
# frame_gate = vector_sampler(
# gr.sizeof_gr_complex * total_subc * config.frame_length, 1 )
# self.connect( ofdm_blocks, frame_sampler, frame_gate,
# self.symbol_output )
# else:
# self.connect( ofdm_blocks, frame_sampler, self.symbol_output )
#
# self.connect( frame_start, delayed_frame_start, ( frame_sampler, 1 ) )
if options.enable_erasure_decision:
frame_gate = frame_sampler.frame_gate
self.symbol_output = frame_sampler
orig_frame_start = frame_start
frame_start = (frame_sampler,1)
self.frame_trigger = frame_start
#terminate_stream(self, self.frame_trigger)
## Pilot block filter
pb_filt = self._pilot_block_filter = fbmc_pilot_block_filter()
self.connect(self.symbol_output,pb_filt)
self.connect(self.frame_trigger,(pb_filt,1))
self.frame_data_trigger = (pb_filt,1)
#self.symbol_output = pb_filt
#if options.log:
#log_to_file(self, pb_filt, "data/pb_filt_out.compl")
if config.fbmc:
pda_in = pb_filt
else:
## Pilot subcarrier filter
ps_filt = self._pilot_subcarrier_filter = pilot_subcarrier_filter()
self.connect(self.symbol_output,ps_filt)
if options.log:
log_to_file(self, ps_filt, "data/ps_filt_out.compl")
pda_in = ps_filt
## Workaround to avoid periodic structure
# for ID decoder
seed(1)
whitener_pn = [randint(0,1) for i in range(used_id_bits*rep_id_bits)]
if not options.enable_erasure_decision:
## ID Block Filter
# Filter ID block, skip data blocks
id_bfilt = self._id_block_filter = vector_sampler(
gr.sizeof_gr_complex * dsubc, 1 )
if not config.frame_id_blocks == 1:
raise SystemExit, "# ID Blocks > 1 not supported"
self.connect( pda_in , id_bfilt )
self.connect( self.frame_data_trigger, ( id_bfilt, 1 ) ) # trigger
#log_to_file( self, id_bfilt, "data/id_bfilt.compl" )
## ID Demapper and Decoder, soft decision
self.id_dec = self._id_decoder = ofdm.coded_bpsk_soft_decoder( dsubc,
used_id_bits, whitener_pn )
self.connect( id_bfilt, self.id_dec )
print "Using coded BPSK soft decoder for ID detection"
else: # options.enable_erasure_decision:
id_bfilt = self._id_block_filter = vector_sampler(
gr.sizeof_gr_complex * total_subc, config.frame_id_blocks )
id_bfilt_trig_delay = 0
for x in range( config.frame_length ):
if x in config.training_data.pilotsym_pos:
id_bfilt_trig_delay += 1
else:
break
print "Position of ID block within complete frame: %d" %(id_bfilt_trig_delay)
assert( id_bfilt_trig_delay > 0 ) # else not supported
id_bfilt_trig = blocks.delay( gr.sizeof_char, id_bfilt_trig_delay )
self.connect( ofdm_blocks, id_bfilt )
self.connect( orig_frame_start, id_bfilt_trig, ( id_bfilt, 1 ) )
self.id_dec = self._id_decoder = ofdm.coded_bpsk_soft_decoder( total_subc,
used_id_bits, whitener_pn, config.training_data.shifted_pilot_tones )
self.connect( id_bfilt, self.id_dec )
print "Using coded BPSK soft decoder for ID detection"
# The threshold block either returns 1.0 if the llr-value from the
# id decoder is below the threshold, else 0.0. Hence we convert this
# into chars, 0 and 1, and use it as trigger for the sampler.
min_llr = ( self.id_dec, 1 )
erasure_threshold = gr.threshold_ff( 10.0, 10.0, 0 ) # FIXME is it the optimal threshold?
erasure_dec = gr.float_to_char()
id_gate = vector_sampler( gr.sizeof_short, 1 )
ctf_gate = vector_sampler( gr.sizeof_float * total_subc, 1 )
self.connect( self.id_dec , id_gate )
self.connect( self.ctf, ctf_gate )
self.connect( min_llr, erasure_threshold, erasure_dec )
self.connect( erasure_dec, ( frame_gate, 1 ) )
self.connect( erasure_dec, ( id_gate, 1 ) )
self.connect( erasure_dec, ( ctf_gate, 1 ) )
self.id_dec = self._id_decoder = id_gate
self.ctf = ctf_gate
print "Erasure decision for IDs is enabled"
if options.log:
id_dec_f = gr.short_to_float()
self.connect(self.id_dec,id_dec_f)
log_to_file(self, id_dec_f, "data/id_dec_out.float")
if options.log:
log_to_file(self, id_bfilt, "data/id_blockfilter_out.compl")
# TODO: refactor names
if options.log:
map_src_f = gr.char_to_float(dsubc)
self.connect(map_src,map_src_f)
log_to_file(self, map_src_f, "data/map_src_out.float")
## Allocation Control
if options.static_allocation: #DEBUG
if options.coding:
mode = 1 # Coding mode 1-9
bitspermode = [0.5,1,1.5,2,3,4,4.5,5,6] # Information bits per mode
bitcount_vec = [(int)(config.data_subcarriers*config.frame_data_blocks*bitspermode[mode-1])]
bitloading = mode
else:
bitloading = 1
bitcount_vec = [config.data_subcarriers*config.frame_data_blocks*bitloading]
#bitcount_vec = [config.data_subcarriers*config.frame_data_blocks]
self.bitcount_src = blocks.vector_source_i(bitcount_vec,True,1)
# 0s for ID block, then data
#bitloading_vec = [0]*dsubc+[0]*(dsubc/2)+[2]*(dsubc/2)
bitloading_vec = [0]*dsubc+[bitloading]*dsubc
bitloading_src = blocks.vector_source_b(bitloading_vec,True,dsubc)
power_vec = [1]*config.data_subcarriers
power_src = blocks.vector_source_f(power_vec,True,dsubc)
else:
self.allocation_buffer = ofdm.allocation_buffer(config.data_subcarriers, config.frame_data_blocks, "tcp://"+options.tx_hostname+":3333",config.coding)
self.bitcount_src = (self.allocation_buffer,0)
bitloading_src = (self.allocation_buffer,1)
power_src = (self.allocation_buffer,2)
self.connect(self.id_dec, self.allocation_buffer)
if options.benchmarking:
self.allocation_buffer.set_allocation([4]*config.data_subcarriers,[1]*config.data_subcarriers)
if options.log:
log_to_file(self, self.bitcount_src, "data/bitcount_src_rx.int")
log_to_file(self, bitloading_src, "data/bitloading_src_rx.char")
log_to_file(self, power_src, "data/power_src_rx.cmplx")
log_to_file(self, self.id_dec, "data/id_dec_rx.short")
## Power Deallocator
pda = self._power_deallocator = multiply_frame_fc(config.frame_data_part, dsubc)
self.connect(pda_in,(pda,0))
self.connect(power_src,(pda,1))
## Demodulator
# if 0:
# ac_vector = [0.0+0.0j]*208
# ac_vector[0] = (2*10**(-0.452))
# ac_vector[3] = (10**(-0.651))
# ac_vector[7] = (10**(-1.151))
# csi_vector_inv=abs(numpy.fft.fft(numpy.sqrt(ac_vector)))**2
# dm_csi = numpy.fft.fftshift(csi_vector_inv) # TODO
dm_csi = [1]*dsubc # TODO
dm_csi = blocks.vector_source_f(dm_csi,True)
## Depuncturer
dp_trig = [0]*(config.frame_data_blocks/2)
dp_trig[0] = 1
dp_trig = blocks.vector_source_b(dp_trig,True) # TODO
if(options.coding):
fo=ofdm.fsm(1,2,[91,121])
if options.interleave:
int_object=trellis.interleaver(2000,666)
deinterlv = trellis.permutation(int_object.K(),int_object.DEINTER(),1,gr.sizeof_float)
demod = self._data_demodulator = generic_softdemapper_vcf(dsubc, config.frame_data_part, config.coding)
#self.connect(dm_csi,blocks.stream_to_vector(gr.sizeof_float,dsubc),(demod,2))
if(options.ideal):
self.connect(dm_csi,blocks.stream_to_vector(gr.sizeof_float,dsubc),(demod,2))
else:
dm_csi_filter = self.dm_csi_filter = filter.single_pole_iir_filter_ff(0.01,dsubc)
self.connect(self.ctf, self.dm_csi_filter,(demod,2))
#log_to_file(self, dm_csi_filter, "data/softs_csi.float")
#self.connect(dm_trig,(demod,3))
else:
demod = self._data_demodulator = generic_demapper_vcb(dsubc, config.frame_data_part)
if options.benchmarking:
# Do receiver benchmarking until the number of frames x symbols are collected
self.connect(pda,blocks.head(gr.sizeof_gr_complex*dsubc, options.N*config.frame_data_blocks),demod)
else:
self.connect(pda,demod)
self.connect(bitloading_src,(demod,1))
if(options.coding):
## Depuncturing
if not options.nopunct:
depuncturing = depuncture_ff(dsubc,0)
frametrigger_bitmap_filter = blocks.vector_source_b([1,0],True)
self.connect(bitloading_src,(depuncturing,1))
self.connect(dp_trig,(depuncturing,2))
## Decoding
chunkdivisor = int(numpy.ceil(config.frame_data_blocks/5.0))
print "Number of chunks at Viterbi decoder: ", chunkdivisor
decoding = self._data_decoder = ofdm.viterbi_combined_fb(fo,dsubc,-1,-1,2,chunkdivisor,[-1,-1,-1,1,1,-1,1,1],ofdm.TRELLIS_EUCLIDEAN)
if options.log and options.coding:
log_to_file(self, decoding, "data/decoded.char")
if not options.nopunct:
log_to_file(self, depuncturing, "data/vit_in.float")
if not options.nopunct:
if options.interleave:
self.connect(demod,deinterlv,depuncturing,decoding)
else:
self.connect(demod,depuncturing,decoding)
else:
self.connect(demod,decoding)
self.connect(self.bitcount_src, multiply_const_ii(1./chunkdivisor), (decoding,1))
if options.scatterplot or options.scatter_plot_before_phase_tracking:
if self.ideal2 is False:
scatter_vec_elem = self._scatter_vec_elem = ofdm.vector_element(dsubc,40)
scatter_s2v = self._scatter_s2v = blocks.stream_to_vector(gr.sizeof_gr_complex,config.frame_data_blocks)
scatter_id_filt = skip(gr.sizeof_gr_complex*dsubc,config.frame_data_blocks)
scatter_id_filt.skip_call(0)
scatter_trig = [0]*config.frame_data_part
scatter_trig[0] = 1
scatter_trig = blocks.vector_source_b(scatter_trig,True)
self.connect(scatter_trig,(scatter_id_filt,1))
self.connect(scatter_vec_elem,scatter_s2v)
if not options.scatter_plot_before_phase_tracking:
print "Enabling Scatterplot for data subcarriers"
self.connect(pda,scatter_id_filt,scatter_vec_elem)
# Work on this
#scatter_sink = ofdm.scatterplot_sink(dsubc)
#self.connect(pda,scatter_sink)
#self.connect(map_src,(scatter_sink,1))
#self.connect(dm_trig,(scatter_sink,2))
#print "Enabled scatterplot gui interface"
self.zmq_probe_scatter = zeromq.pub_sink(gr.sizeof_gr_complex,config.frame_data_blocks, "tcp://*:5560")
self.connect(scatter_s2v, blocks.keep_one_in_n(gr.sizeof_gr_complex*config.frame_data_blocks,20), self.zmq_probe_scatter)
else:
print "Enabling Scatterplot for data before phase tracking"
inner_rx = inner_receiver.before_phase_tracking
#scatter_sink2 = ofdm.scatterplot_sink(dsubc,"phase_tracking")
op = copy.copy(options)
op.enable_erasure_decision = False
new_framesampler = ofdm_frame_sampler(op)
self.connect( inner_rx, new_framesampler )
self.connect( orig_frame_start, (new_framesampler,1) )
new_ps_filter = pilot_subcarrier_filter()
new_pb_filter = fbmc_pilot_block_filter()
self.connect( (new_framesampler,1), (new_pb_filter,1) )
self.connect( new_framesampler, new_pb_filter,
new_ps_filter, scatter_id_filt, scatter_vec_elem )
#self.connect( new_ps_filter, scatter_sink2 )
#self.connect( map_src, (scatter_sink2,1))
#self.connect( dm_trig, (scatter_sink2,2))
if options.log:
if(options.coding):
log_to_file(self, demod, "data/data_stream_out.float")
else:
data_f = gr.char_to_float()
self.connect(demod,data_f)
log_to_file(self, data_f, "data/data_stream_out.float")
if options.sfo_feedback:
used_id_bits = 8
rep_id_bits = config.data_subcarriers/used_id_bits
seed(1)
whitener_pn = [randint(0,1) for i in range(used_id_bits*rep_id_bits)]
id_enc = ofdm.repetition_encoder_sb(used_id_bits,rep_id_bits,whitener_pn)
self.connect( self.id_dec, id_enc )
id_mod = ofdm_bpsk_modulator(dsubc)
self.connect( id_enc, id_mod )
id_mod_conj = gr.conjugate_cc(dsubc)
self.connect( id_mod, id_mod_conj )
id_mult = blocks.multiply_vcc(dsubc)
self.connect( id_bfilt, ( id_mult,0) )
self.connect( id_mod_conj, ( id_mult,1) )
# id_mult_avg = filter.single_pole_iir_filter_cc(0.01,dsubc)
# self.connect( id_mult, id_mult_avg )
id_phase = gr.complex_to_arg(dsubc)
self.connect( id_mult, id_phase )
log_to_file( self, id_phase, "data/id_phase.float" )
est=ofdm.LS_estimator_straight_slope(dsubc)
self.connect(id_phase,est)
slope=blocks.multiply_const_ff(1e6/2/3.14159265)
self.connect( (est,0), slope )
log_to_file( self, slope, "data/slope.float" )
log_to_file( self, (est,1), "data/offset.float" )
# ------------------------------------------------------------------------ #
# Display some information about the setup
if config._verbose:
self._print_verbage()
## debug logging ##
if options.log:
# log_to_file(self,self.ofdm_symbols,"data/unequalized_rx_ofdm_symbols.compl")
# log_to_file(self,self.ofdm_symbols,"data/unequalized_rx_ofdm_symbols.float",mag=True)
fftlen = 256
my_window = window.hamming(fftlen) #.blackmanharris(fftlen)
rxs_sampler = vector_sampler(gr.sizeof_gr_complex,fftlen)
rxs_sampler_vect = concatenate([[1],[0]*49])
rxs_trigger = blocks.vector_source_b(rxs_sampler_vect.tolist(),True)
rxs_window = blocks.multiply_const_vcc(my_window)
rxs_spectrum = gr.fft_vcc(fftlen,True,[],True)
rxs_mag = gr.complex_to_mag(fftlen)
rxs_avg = filter.single_pole_iir_filter_ff(0.01,fftlen)
#rxs_logdb = blocks.nlog10_ff(20.0,fftlen,-20*log10(fftlen))
rxs_logdb = gr.kludge_copy( gr.sizeof_float * fftlen )
rxs_decimate_rate = gr.keep_one_in_n(gr.sizeof_float*fftlen,1)
self.connect(rxs_trigger,(rxs_sampler,1))
self.connect(self.input,rxs_sampler,rxs_window,
rxs_spectrum,rxs_mag,rxs_avg,rxs_logdb, rxs_decimate_rate)
log_to_file( self, rxs_decimate_rate, "data/psd_input.float" )
#output branches
self.publish_rx_performance_measure()
def __init__(self, options, log=False):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
L = block_header.mm_periodic_parts
frame_data_blocks = options.data_blocks
## Set Input/Output signature
gr.hier_block2.__init__(
self,
"ofdm_inner_receiver",
gr.io_signature(2, 2, gr.sizeof_gr_complex),
gr.io_signature5(
5,
5,
gr.sizeof_gr_complex * total_subc, # OFDM blocks
gr.sizeof_char, # Frame start
gr.sizeof_float * total_subc, # Normalized |CTF|^2
gr.sizeof_char, # Frame start
gr.sizeof_float * total_subc)) # Normalized |CTF|^2
## Input and output ports
self.input = rx_input = (self, 0)
self.input2 = rx2_input = (self, 1)
out_ofdm_blocks = (self, 0)
out_frame_start = (self, 1)
out_disp_ctf = (self, 2)
out_frame_start2 = (self, 3)
out_disp_ctf2 = (self, 4)
## pre-FFT processing
## Compute autocorrelations for S&C preamble
## and cyclic prefix
sc_metric = autocorrelator(fft_length / 2, fft_length / 2)
gi_metric = autocorrelator(fft_length, cp_length)
self.connect(rx_input, sc_metric)
self.connect(rx_input, gi_metric)
sc_metric2 = autocorrelator(fft_length / 2, fft_length / 2)
gi_metric2 = autocorrelator(fft_length, cp_length)
self.connect(rx2_input, sc_metric2)
self.connect(rx2_input, gi_metric2)
## Sync. Output contains OFDM blocks
sync = ofdm.time_sync(fft_length, cp_length)
self.connect(rx_input, (sync, 0))
self.connect(sc_metric, (sync, 1))
self.connect(gi_metric, (sync, 2))
ofdm_blocks = (sync, 0)
frame_start = (sync, 1)
sync2 = ofdm.time_sync(fft_length, cp_length)
self.connect(rx2_input, (sync2, 0))
self.connect(sc_metric2, (sync2, 1))
self.connect(gi_metric2, (sync2, 2))
ofdm_blocks2 = (sync2, 0)
frame_start2 = (sync2, 1)
if options.disable_time_sync or options.ideal:
terminate_stream(self, ofdm_blocks)
terminate_stream(self, ofdm_blocks2)
terminate_stream(self, frame_start)
terminate_stream(self, frame_start2)
serial_to_parallel = blocks.stream_to_vector(
gr.sizeof_gr_complex, block_length)
serial_to_parallel2 = blocks.stream_to_vector(
gr.sizeof_gr_complex, block_length)
discard_cp = ofdm.vector_mask(block_length, cp_length, fft_length,
[])
discard_cp2 = ofdm.vector_mask(block_length, cp_length, fft_length,
[])
ofdm_blocks = discard_cp
ofdm_blocks2 = discard_cp2
self.connect(rx_input, serial_to_parallel, discard_cp)
self.connect(rx2_input, serial_to_parallel2, discard_cp2)
frame_start = [0] * frame_length
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start, True)
frame_start2 = [0] * frame_length
frame_start2[0] = 1
frame_start2 = blocks.vector_source_b(frame_start2, True)
print "Disabled time synchronization stage"
## Extract preamble, feed to Morelli & Mengali frequency offset estimator
assert (block_header.mm_preamble_pos == 0)
morelli_foe = ofdm.mm_frequency_estimator(fft_length, L)
sampler_preamble = ofdm.vector_sampler(
gr.sizeof_gr_complex * fft_length, 1)
self.connect(ofdm_blocks, (sampler_preamble, 0))
self.connect(frame_start, (sampler_preamble, 1))
self.connect(sampler_preamble, morelli_foe)
freq_offset = morelli_foe
morelli_foe2 = ofdm.mm_frequency_estimator(fft_length, L)
sampler_preamble2 = ofdm.vector_sampler(
gr.sizeof_gr_complex * fft_length, 1)
self.connect(ofdm_blocks2, (sampler_preamble2, 0))
self.connect(frame_start2, (sampler_preamble2, 1))
self.connect(sampler_preamble2, morelli_foe2)
freq_offset2 = morelli_foe2
## Adaptive LMS FIR filtering of frequency offset
lms_fir = ofdm.lms_fir_ff(20, 1e-3) # TODO: verify parameter choice
self.connect(freq_offset, lms_fir)
freq_offset = lms_fir
lms_fir2 = ofdm.lms_fir_ff(20, 1e-3) # TODO: verify parameter choice
self.connect(freq_offset2, lms_fir2)
freq_offset2 = lms_fir2
# log_to_file(self, lms_fir, "data/lms_fir.float")
# log_to_file(self, lms_fir2, "data/lms_fir2.float")
if options.disable_freq_sync or options.ideal:
terminate_stream(self, freq_offset)
terminate_stream(self, freq_offset2)
freq_offset = blocks.vector_source_f([0.0], True)
freq_offset2 = blocks.vector_source_f([0.0], True)
print "Disabled frequency synchronization stage"
## Correct frequency shift, feed-forward structure
frequency_shift = ofdm.frequency_shift_vcc(fft_length,
-1.0 / fft_length,
cp_length)
self.connect(ofdm_blocks, (frequency_shift, 0))
self.connect(freq_offset, (frequency_shift, 1))
self.connect(frame_start, (frequency_shift, 2))
ofdm_blocks = frequency_shift
frequency_shift2 = ofdm.frequency_shift_vcc(fft_length,
-1.0 / fft_length,
cp_length)
self.connect(ofdm_blocks2, (frequency_shift2, 0))
self.connect(freq_offset2, (frequency_shift2, 1))
self.connect(frame_start2, (frequency_shift2, 2))
ofdm_blocks2 = frequency_shift2
## FFT
fft = fft_blocks.fft_vcc(fft_length, True, [], True)
self.connect(ofdm_blocks, fft)
ofdm_blocks = fft
fft2 = fft_blocks.fft_vcc(fft_length, True, [], True)
self.connect(ofdm_blocks2, fft2)
ofdm_blocks2 = fft2
## Remove virtual subcarriers
if fft_length > data_subc:
subcarrier_mask = ofdm.vector_mask(fft_length, virtual_subc / 2,
total_subc, [])
self.connect(ofdm_blocks, subcarrier_mask)
ofdm_blocks = subcarrier_mask
subcarrier_mask2 = ofdm.vector_mask(fft_length, virtual_subc / 2,
total_subc, [])
self.connect(ofdm_blocks2, subcarrier_mask2)
ofdm_blocks2 = subcarrier_mask2
## Least Squares estimator for channel transfer function (CTF)
# if options.logcir:
# log_to_file( self, ofdm_blocks, "data/OFDM_Blocks.compl" )
# inv_preamble_fd = numpy.array( block_header.pilotsym_fd[
# block_header.channel_estimation_pilot[0] ] )
# print "Channel estimation pilot: ", inv_preamble_fd
# inv_preamble_fd = 1. / inv_preamble_fd
# LS_channel_estimator0 = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
# self.connect( ofdm_blocks, LS_channel_estimator0, blocks.null_sink(gr.sizeof_gr_complex*total_subc))
# log_to_file( self, LS_channel_estimator0, "data/OFDM_Blocks_eq.compl" )
## post-FFT processing
if options.est_preamble == 1:
## extract channel estimation preamble from frame
chest_pre_trigger = blocks.delay(gr.sizeof_char, 1)
sampled_chest_preamble = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
self.connect(frame_start, chest_pre_trigger)
self.connect(chest_pre_trigger, (sampled_chest_preamble, 1))
self.connect(ofdm_blocks, (sampled_chest_preamble, 0))
chest_pre_trigger2 = blocks.delay(gr.sizeof_char, 1)
sampled_chest_preamble2 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
self.connect(frame_start2, chest_pre_trigger2)
self.connect(chest_pre_trigger2, (sampled_chest_preamble2, 1))
self.connect(ofdm_blocks2, (sampled_chest_preamble2, 0))
## Least Squares estimator for channel transfer function (CTF)
# Taking inverse for estimating h11 (h12)
inv_preamble_fd_1 = numpy.array(block_header.pilotsym_fd_1[
block_header.channel_estimation_pilot[0]])
inv_preamble_fd_1 = inv_preamble_fd_1[0::2]
# Taking inverse for estimating h21 (h22)
inv_preamble_fd_2 = numpy.array(block_header.pilotsym_fd_2[
block_header.channel_estimation_pilot[0]])
inv_preamble_fd_2 = inv_preamble_fd_2[1::2]
inv_preamble_fd_1 = 1. / inv_preamble_fd_1
inv_preamble_fd_2 = 1. / inv_preamble_fd_2
## Least Squares estimator for channel transfer function (CTF)
dd = []
for i in range(total_subc / 2):
dd.extend([i * 2])
skip_block_1 = ofdm.int_skip(total_subc, 2, 0)
skip_block_2 = ofdm.int_skip(total_subc, 2, 1)
# inta_estim_1 = ofdm.interpolator(total_subc,2,dd)
# inta_estim_2 = ofdm.interpolator(total_subc,2,dd)
LS_channel_estimator_1 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_1))
LS_channel_estimator_2 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_2))
self.connect(sampled_chest_preamble, skip_block_1,
LS_channel_estimator_1) #,inta_estim_1 )
self.connect(sampled_chest_preamble, skip_block_2,
LS_channel_estimator_2) #,inta_estim_2 )
estimated_CTF_1 = LS_channel_estimator_1 # h0
estimated_CTF_2 = LS_channel_estimator_2 # h1
skip_block_3 = ofdm.int_skip(total_subc, 2, 0)
skip_block_4 = ofdm.int_skip(total_subc, 2, 1)
# inta_estim_3 = ofdm.interpolator(total_subc,2,dd)
# inta_estim_4 = ofdm.interpolator(total_subc,2,dd)
LS_channel_estimator_3 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_1))
LS_channel_estimator_4 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_2))
self.connect(sampled_chest_preamble2, skip_block_3,
LS_channel_estimator_3) #,inta_estim_3 )
self.connect(sampled_chest_preamble2, skip_block_4,
LS_channel_estimator_4) #,inta_estim_4 )
estimated_CTF_3 = LS_channel_estimator_3 # h2
estimated_CTF_4 = LS_channel_estimator_4 # h3
if not options.disable_ctf_enhancer:
# if options.logcir:
# ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
# self.connect( estimated_CTF, ifft1,blocks.null_sink(gr.sizeof_gr_complex*total_subc))
# summ1 = ofdm.vector_sum_vcc(total_subc)
# c2m =gr.complex_to_mag(total_subc)
# self.connect( estimated_CTF,summ1 ,blocks.null_sink(gr.sizeof_gr_complex))
# self.connect( estimated_CTF, c2m,blocks.null_sink(gr.sizeof_float*total_subc))
# log_to_file( self, ifft1, "data/CIR1.compl" )
# log_to_file( self, summ1, "data/CTFsumm1.compl" )
# log_to_file( self, estimated_CTF, "data/CTF1.compl" )
# log_to_file( self, c2m, "data/CTFmag1.float" )
## MSE enhancer
ctf_mse_enhancer_1 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
ctf_mse_enhancer_2 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
self.connect(estimated_CTF_1, ctf_mse_enhancer_1)
self.connect(estimated_CTF_2, ctf_mse_enhancer_2)
ctf_mse_enhancer_3 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
ctf_mse_enhancer_4 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
self.connect(estimated_CTF_3, ctf_mse_enhancer_3)
self.connect(estimated_CTF_4, ctf_mse_enhancer_4)
estimated_CTF_1 = ctf_mse_enhancer_1
estimated_CTF_2 = ctf_mse_enhancer_2
estimated_CTF_3 = ctf_mse_enhancer_3
estimated_CTF_4 = ctf_mse_enhancer_4
print "Disabled CTF MSE enhancer"
ctf_postprocess_1 = ofdm.postprocess_CTF_estimate(total_subc / 2)
self.connect(estimated_CTF_1, (ctf_postprocess_1, 0))
ctf_postprocess_2 = ofdm.postprocess_CTF_estimate(total_subc / 2)
self.connect(estimated_CTF_2, (ctf_postprocess_2, 0))
ctf_postprocess_3 = ofdm.postprocess_CTF_estimate(total_subc / 2)
self.connect(estimated_CTF_3, (ctf_postprocess_3, 0))
ctf_postprocess_4 = ofdm.postprocess_CTF_estimate(total_subc / 2)
self.connect(estimated_CTF_4, (ctf_postprocess_4, 0))
inv_CTF_1 = (ctf_postprocess_1, 0)
disp_CTF_1 = (ctf_postprocess_1, 1)
inv_CTF_2 = (ctf_postprocess_2, 0)
disp_CTF_2 = (ctf_postprocess_2, 1)
inv_CTF_3 = (ctf_postprocess_3, 0)
disp_CTF_3 = (ctf_postprocess_3, 1)
inv_CTF_4 = (ctf_postprocess_4, 0)
disp_CTF_4 = (ctf_postprocess_4, 1)
disp_CTF_RX0 = blocks.add_ff(total_subc / 2)
disp_CTF_RX1 = blocks.add_ff(total_subc / 2)
self.connect(disp_CTF_1, (disp_CTF_RX0, 0))
self.connect(disp_CTF_2, (disp_CTF_RX0, 1))
self.connect(disp_CTF_3, (disp_CTF_RX1, 0))
self.connect(disp_CTF_4, (disp_CTF_RX1, 1))
terminate_stream(self, disp_CTF_RX0)
terminate_stream(self, disp_CTF_RX1)
disp_CTF_RX0 = blocks.null_source(gr.sizeof_float * total_subc)
disp_CTF_RX1 = blocks.null_source(gr.sizeof_float * total_subc)
## Channel Equalizer
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
#log_to_file(self, ofdm_blocks2, "data/vec_mask2.compl")
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03(
total_subc, pilot_subc, nondata_blocks, pilot_subcarriers, 0)
phase_tracking2 = ofdm.lms_phase_tracking_03(
total_subc, pilot_subc, nondata_blocks, pilot_subcarriers, 0)
##phase_tracking = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
## nondata_blocks )
##phase_tracking2 = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
## nondata_blocks )
# self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
# self.connect( ofdm_blocks2, ( phase_tracking, 1 ))
# self.connect( inv_CTF_1, ( phase_tracking, 2 ) )
# self.connect( inv_CTF_3, ( phase_tracking, 3 ) )
# self.connect( frame_start, ( phase_tracking, 4 ) )
# self.connect( frame_start2, ( phase_tracking, 5) )
#
# self.connect( ofdm_blocks2, ( phase_tracking2, 0 ) )
# self.connect( ofdm_blocks, ( phase_tracking2, 1 ))
# self.connect( inv_CTF_3, ( phase_tracking2, 2 ) )
# self.connect( inv_CTF_1, ( phase_tracking2, 3 ) )
# self.connect( frame_start2, ( phase_tracking2, 4 ) )
# self.connect( frame_start, ( phase_tracking2, 5 ) )
self.connect(ofdm_blocks, (phase_tracking, 0))
self.connect(inv_CTF_1, (phase_tracking, 1))
self.connect(frame_start, (phase_tracking, 2))
self.connect(ofdm_blocks2, (phase_tracking2, 0))
self.connect(inv_CTF_3, (phase_tracking2, 1))
self.connect(frame_start2, (phase_tracking2, 2))
#ofdm_blocks = phase_tracking
#ofdm_blocks2 = phase_tracking2
self.connect(phase_tracking,
blocks.null_sink(gr.sizeof_gr_complex * total_subc))
self.connect(phase_tracking2,
blocks.null_sink(gr.sizeof_gr_complex * total_subc))
terminate_stream(self, inv_CTF_2)
terminate_stream(self, inv_CTF_4)
#terminate_stream(self, inv_CTF_1)
#terminate_stream(self, inv_CTF_3)
terminate_stream(self, estimated_CTF_3)
terminate_stream(self, estimated_CTF_4)
##terminate_stream(self, (phase_tracking,1))
##terminate_stream(self, (phase_tracking2,1))
'''equalizer = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( ofdm_blocks2, ( equalizer, 1 ) )
self.connect( inv_CTF_1, ( equalizer, 2 ) )
self.connect( inv_CTF_2, ( equalizer, 3 ) )
self.connect( inv_CTF_3, ( equalizer, 4 ) )
self.connect( inv_CTF_4, ( equalizer, 5 ) )
self.connect( frame_start, ( equalizer, 6 ) )
self.connect( frame_start2, ( equalizer, 7 ) )
ofdm_blocks = equalizer'''
terminate_stream(self, inv_CTF_1)
terminate_stream(self, inv_CTF_3)
equalizer = ofdm.channel_equalizer_mimo_2(total_subc)
self.connect(ofdm_blocks, (equalizer, 0))
self.connect(estimated_CTF_1, (equalizer, 1))
self.connect(estimated_CTF_2, (equalizer, 2))
self.connect(frame_start, (equalizer, 3))
ofdm_blocks = equalizer
equalizer2 = ofdm.channel_equalizer_mimo_2(total_subc)
self.connect(ofdm_blocks2, (equalizer2, 0))
self.connect(estimated_CTF_3, (equalizer2, 1))
self.connect(estimated_CTF_4, (equalizer2, 2))
self.connect(frame_start2, (equalizer2, 3))
ofdm_blocks2 = equalizer2
#ofdm_blocks = equalizer
#ofdm_blocks2 = equalizer2
#log_to_file(self, equalizer,"data/equalizer.compl")
#log_to_file(self, ofdm_blocks2,"data/equalizer.compl")
#log_to_file(self, ofdm_blocks,"data/equalizer2.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
'''
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
phase_tracking = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer, ( phase_tracking, 0 ) )
self.connect( frame_start, ( phase_tracking, 1 ) )
phase_tracking2 = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer2, ( phase_tracking2, 0 ) )
self.connect( frame_start2, ( phase_tracking2, 1 ) )
# if options.scatter_plot_before_phase_tracking:
# self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
ofdm_blocks2 = phase_tracking2
log_to_file(self,phase_tracking, "data/phase_tracking.compl")
'''
combine = blocks.add_cc(config.subcarriers)
self.connect(ofdm_blocks, (combine, 0))
self.connect(ofdm_blocks2, (combine, 1))
norm_val = [0.5] * 208
norm = ofdm.multiply_const_vcc(norm_val)
self.connect(combine, norm)
ofdm_blocks = norm
## div = gr.multiply_cc(config.subcarriers)
## const = blocks.vector_source_c([[0.5+0]*config.subcarriers],True)
## self.connect(ofdm_blocks,div)
## self.connect(const,(div,1))
## ofdm_blocks=div
# log_to_file(self,combine,"data/combine.compl")
## Output connections
self.connect(ofdm_blocks, out_ofdm_blocks)
self.connect(frame_start, out_frame_start)
self.connect(disp_CTF_RX0, out_disp_ctf)
self.connect(frame_start2, out_frame_start2)
self.connect(disp_CTF_RX1, out_disp_ctf2)
else:
## extract channel estimation preamble from frame
chest_pre_trigger_11 = blocks.delay(gr.sizeof_char, 1)
chest_pre_trigger_12 = blocks.delay(gr.sizeof_char, 2)
sampled_chest_preamble_11 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
sampled_chest_preamble_12 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
self.connect(frame_start, chest_pre_trigger_11)
self.connect(chest_pre_trigger_11, (sampled_chest_preamble_11, 1))
self.connect(ofdm_blocks, (sampled_chest_preamble_11, 0))
self.connect(frame_start, chest_pre_trigger_12)
self.connect(chest_pre_trigger_12, (sampled_chest_preamble_12, 1))
self.connect(ofdm_blocks, (sampled_chest_preamble_12, 0))
chest_pre_trigger_21 = blocks.delay(gr.sizeof_char, 1)
chest_pre_trigger_22 = blocks.delay(gr.sizeof_char, 2)
sampled_chest_preamble_21 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
sampled_chest_preamble_22 = \
ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1 )
self.connect(frame_start2, chest_pre_trigger_21)
self.connect(chest_pre_trigger_21, (sampled_chest_preamble_21, 1))
self.connect(ofdm_blocks2, (sampled_chest_preamble_21, 0))
self.connect(frame_start2, chest_pre_trigger_22)
self.connect(chest_pre_trigger_22, (sampled_chest_preamble_22, 1))
self.connect(ofdm_blocks2, (sampled_chest_preamble_22, 0))
# Taking inverse for estimating h11 (h12)
inv_preamble_fd_1 = numpy.array(block_header.pilotsym_fd_1[
block_header.channel_estimation_pilot[0]])
#inv_preamble_fd_1 = inv_preamble_fd_1[0::2]
# Taking inverse for estimating h21 (h22)
inv_preamble_fd_2 = numpy.array(block_header.pilotsym_fd_2[
block_header.channel_estimation_pilot[0] + 1])
#inv_preamble_fd_2 = inv_preamble_fd_2[1::2]
inv_preamble_fd_1 = 1. / inv_preamble_fd_1
inv_preamble_fd_2 = 1. / inv_preamble_fd_2
# dd = []
#for i in range (total_subc/2):
# dd.extend([i*2])
skip_block_11 = ofdm.int_skip(total_subc, 2, 0)
skip_block_111 = ofdm.int_skip(total_subc, 2, 0)
skip_block_12 = ofdm.int_skip(total_subc, 2, 1)
# inta_estim_1 = ofdm.interpolator(total_subc,2,dd)
# inta_estim_2 = ofdm.interpolator(total_subc,2,dd)
LS_channel_estimator_11 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_1))
LS_channel_estimator_12 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_2))
self.connect(sampled_chest_preamble_11,
LS_channel_estimator_11) #,inta_estim_1 )
self.connect(sampled_chest_preamble_12,
LS_channel_estimator_12) #,inta_estim_2 )
estimated_CTF_11 = LS_channel_estimator_11 # h0
estimated_CTF_12 = LS_channel_estimator_12 # h1
skip_block_21 = ofdm.int_skip(total_subc, 2, 0)
skip_block_211 = ofdm.int_skip(total_subc, 2, 0)
skip_block_22 = ofdm.int_skip(total_subc, 2, 1)
# inta_estim_3 = ofdm.interpolator(total_subc,2,dd)
# inta_estim_4 = ofdm.interpolator(total_subc,2,dd)
LS_channel_estimator_21 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_1))
LS_channel_estimator_22 = ofdm.multiply_const_vcc(
list(inv_preamble_fd_2))
self.connect(sampled_chest_preamble_21,
LS_channel_estimator_21) #,inta_estim_3 )
self.connect(sampled_chest_preamble_22,
LS_channel_estimator_22) #,inta_estim_4 )
estimated_CTF_21 = LS_channel_estimator_21 # h2
estimated_CTF_22 = LS_channel_estimator_22 # h3
if not options.disable_ctf_enhancer:
# if options.logcir:
# ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
# self.connect( estimated_CTF, ifft1,blocks.null_sink(gr.sizeof_gr_complex*total_subc))
# summ1 = ofdm.vector_sum_vcc(total_subc)
# c2m =gr.complex_to_mag(total_subc)
# self.connect( estimated_CTF,summ1 ,blocks.null_sink(gr.sizeof_gr_complex))
# self.connect( estimated_CTF, c2m,blocks.null_sink(gr.sizeof_float*total_subc))
# log_to_file( self, ifft1, "data/CIR1.compl" )
# log_to_file( self, summ1, "data/CTFsumm1.compl" )
# log_to_file( self, estimated_CTF, "data/CTF1.compl" )
# log_to_file( self, c2m, "data/CTFmag1.float" )
## MSE enhancer
ctf_mse_enhancer_11 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
ctf_mse_enhancer_12 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
self.connect(estimated_CTF_11, ctf_mse_enhancer_11)
self.connect(estimated_CTF_12, ctf_mse_enhancer_12)
ctf_mse_enhancer_21 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
ctf_mse_enhancer_22 = ofdm.CTF_MSE_enhancer(
total_subc, cp_length + cp_length)
self.connect(estimated_CTF_21, ctf_mse_enhancer_21)
self.connect(estimated_CTF_22, ctf_mse_enhancer_22)
estimated_CTF_11 = ctf_mse_enhancer_11
estimated_CTF_12 = ctf_mse_enhancer_12
estimated_CTF_21 = ctf_mse_enhancer_21
estimated_CTF_22 = ctf_mse_enhancer_22
print "Disabled CTF MSE enhancer"
ctf_postprocess_11 = ofdm.postprocess_CTF_estimate(total_subc)
self.connect(estimated_CTF_11, (ctf_postprocess_11, 0))
ctf_postprocess_12 = ofdm.postprocess_CTF_estimate(total_subc)
self.connect(estimated_CTF_12, (ctf_postprocess_12, 0))
ctf_postprocess_21 = ofdm.postprocess_CTF_estimate(total_subc)
self.connect(estimated_CTF_21, (ctf_postprocess_21, 0))
ctf_postprocess_22 = ofdm.postprocess_CTF_estimate(total_subc)
self.connect(estimated_CTF_22, (ctf_postprocess_22, 0))
inv_CTF_11 = (ctf_postprocess_11, 0)
disp_CTF_11 = (ctf_postprocess_11, 1)
inv_CTF_12 = (ctf_postprocess_12, 0)
disp_CTF_12 = (ctf_postprocess_12, 1)
inv_CTF_21 = (ctf_postprocess_21, 0)
disp_CTF_21 = (ctf_postprocess_21, 1)
inv_CTF_22 = (ctf_postprocess_22, 0)
disp_CTF_22 = (ctf_postprocess_22, 1)
#disp_CTF_RX0 = blocks.add_ff(total_subc)
#disp_CTF_RX1 = blocks.add_ff(total_subc)
#self.connect ( disp_CTF_11, (disp_CTF_RX0, 0) )
#self.connect ( disp_CTF_12, (disp_CTF_RX0, 1) )
#self.connect ( disp_CTF_21, (disp_CTF_RX1, 0) )
#self.connect ( disp_CTF_22, (disp_CTF_RX1, 1) )
terminate_stream(self, disp_CTF_21)
terminate_stream(self, disp_CTF_22)
disp_CTF_RX0 = disp_CTF_11
disp_CTF_RX1 = disp_CTF_12
## Channel Equalizer
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
#log_to_file(self, ofdm_blocks2, "data/vec_mask2.compl")
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03(
total_subc, pilot_subc, nondata_blocks, pilot_subcarriers, 0)
phase_tracking2 = ofdm.lms_phase_tracking_03(
total_subc, pilot_subc, nondata_blocks, pilot_subcarriers, 0)
##phase_tracking = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
## nondata_blocks )
##phase_tracking2 = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
## nondata_blocks )
# self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
# self.connect( ofdm_blocks2, ( phase_tracking, 1 ))
# self.connect( inv_CTF_1, ( phase_tracking, 2 ) )
# self.connect( inv_CTF_3, ( phase_tracking, 3 ) )
# self.connect( frame_start, ( phase_tracking, 4 ) )
# self.connect( frame_start2, ( phase_tracking, 5) )
#
# self.connect( ofdm_blocks2, ( phase_tracking2, 0 ) )
# self.connect( ofdm_blocks, ( phase_tracking2, 1 ))
# self.connect( inv_CTF_3, ( phase_tracking2, 2 ) )
# self.connect( inv_CTF_1, ( phase_tracking2, 3 ) )
# self.connect( frame_start2, ( phase_tracking2, 4 ) )
# self.connect( frame_start, ( phase_tracking2, 5 ) )
self.connect(ofdm_blocks, (phase_tracking, 0))
self.connect(inv_CTF_11, skip_block_111, (phase_tracking, 1))
self.connect(frame_start, (phase_tracking, 2))
self.connect(ofdm_blocks2, (phase_tracking2, 0))
self.connect(inv_CTF_21, skip_block_211, (phase_tracking2, 1))
self.connect(frame_start2, (phase_tracking2, 2))
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
ofdm_blocks2 = phase_tracking2
self.connect(phase_tracking,
blocks.null_sink(gr.sizeof_gr_complex * total_subc))
self.connect(phase_tracking2,
blocks.null_sink(gr.sizeof_gr_complex * total_subc))
terminate_stream(self, inv_CTF_12)
terminate_stream(self, inv_CTF_22)
#terminate_stream(self, inv_CTF_1)
#terminate_stream(self, inv_CTF_3)
#terminate_stream(self, estimated_CTF_21)
#terminate_stream(self, estimated_CTF_22)
##terminate_stream(self, (phase_tracking,1))
##terminate_stream(self, (phase_tracking2,1))
equalizer = ofdm.channel_equalizer_mimo_3(total_subc)
self.connect(ofdm_blocks, (equalizer, 0))
self.connect(ofdm_blocks2, (equalizer, 1))
self.connect(estimated_CTF_11, skip_block_11, (equalizer, 2))
self.connect(estimated_CTF_12, skip_block_12, (equalizer, 3))
self.connect(estimated_CTF_21, skip_block_21, (equalizer, 4))
self.connect(estimated_CTF_22, skip_block_22, (equalizer, 5))
self.connect(frame_start, (equalizer, 6))
self.connect(frame_start, (equalizer, 7))
ofdm_blocks = equalizer
#terminate_stream(self, inv_CTF_11)
#terminate_stream(self, inv_CTF_21)
'''equalizer = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( estimated_CTF_11, skip_block_11, ( equalizer, 1 ) )
self.connect( estimated_CTF_12, skip_block_12, ( equalizer, 2 ) )
self.connect( frame_start, ( equalizer, 3 ) )
ofdm_blocks = equalizer
equalizer2 = ofdm.channel_equalizer_mimo_2( total_subc )
self.connect( ofdm_blocks2, ( equalizer2, 0 ) )
self.connect( estimated_CTF_21, skip_block_21, ( equalizer2, 1 ) )
self.connect( estimated_CTF_22, skip_block_22, ( equalizer2, 2 ) )
self.connect( frame_start2, ( equalizer2, 3 ) )
ofdm_blocks2 = equalizer2'''
#ofdm_blocks = equalizer
#ofdm_blocks2 = equalizer2
#log_to_file(self, equalizer,"data/equalizer.compl")
#log_to_file(self, ofdm_blocks2,"data/equalizer.compl")
#log_to_file(self, ofdm_blocks,"data/equalizer2.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
'''
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
pilot_subc = block_header.pilot_tones
phase_tracking = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer, ( phase_tracking, 0 ) )
self.connect( frame_start, ( phase_tracking, 1 ) )
phase_tracking2 = ofdm.LMS_phase_tracking2( total_subc, pilot_subc,
nondata_blocks )
self.connect( equalizer2, ( phase_tracking2, 0 ) )
self.connect( frame_start2, ( phase_tracking2, 1 ) )
# if options.scatter_plot_before_phase_tracking:
# self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
ofdm_blocks2 = phase_tracking2
log_to_file(self,phase_tracking, "data/phase_tracking.compl")
'''
'''combine = blocks.add_cc(config.subcarriers)
self.connect(ofdm_blocks, (combine,0))
self.connect(ofdm_blocks2, (combine,1))
norm_val = [0.5]*config.subcarriers
norm = ofdm.multiply_const_vcc( norm_val)
self.connect(combine,norm)
ofdm_blocks = norm'''
## div = gr.multiply_cc(config.subcarriers)
## const = blocks.vector_source_c([[0.5+0]*config.subcarriers],True)
## self.connect(ofdm_blocks,div)
## self.connect(const,(div,1))
## ofdm_blocks=div
# log_to_file(self,combine,"data/combine.compl")
## Output connections
self.connect(ofdm_blocks, out_ofdm_blocks)
self.connect(frame_start, out_frame_start)
self.connect(disp_CTF_RX0, out_disp_ctf)
self.connect(frame_start2, out_frame_start2)
self.connect(disp_CTF_RX1, out_disp_ctf2)
def __init__( self, options, log = False ):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
dc_null = config.dc_null
L = block_header.mm_periodic_parts
## Set Input/Output signature
gr.hier_block2.__init__( self,
"ofdm_inner_receiver",
gr.io_signature(
1, 1,
gr.sizeof_gr_complex ),
gr.io_signaturev(
4, 4,
[gr.sizeof_gr_complex * total_subc, # OFDM blocks
gr.sizeof_char, # Frame start
gr.sizeof_float * total_subc,
gr.sizeof_float] ) ) # Normalized |CTF|^2
## Input and output ports
self.input = rx_input = self
out_ofdm_blocks = ( self, 0 )
out_frame_start = ( self, 1 )
out_disp_ctf = ( self, 2 )
out_disp_cfo = ( self, 3 )
## pre-FFT processing
if options.ideal is False and options.ideal2 is False:
if options.old_receiver is False:
## Compute autocorrelations for S&C preamble
## and cyclic prefix
self._sc_metric = sc_metric = autocorrelator( fft_length/2, fft_length/2 )
self._gi_metric = gi_metric = autocorrelator( fft_length, cp_length )
self.connect( rx_input, sc_metric )
self.connect( rx_input, gi_metric )
## Sync. Output contains OFDM blocks
sync = ofdm.time_sync( fft_length, cp_length )
self.connect( rx_input, ( sync, 0 ) )
self.connect( sc_metric, ( sync, 1 ) )
self.connect( gi_metric, ( sync, 2 ) )
ofdm_blocks = ( sync, 0 )
frame_start = ( sync, 1 )
#log_to_file( self, ( sync, 1 ), "data/peak_detector.char" )
else:
#Testing old/new metric
self.tm = schmidl.recursive_timing_metric(fft_length)
self.connect( self.input, self.tm)
#log_to_file( self, self.tm, "data/rec_sc_metric_ofdm.float" )
timingmetric_shift = -2#int(-cp_length/4)# 0#-2 #int(-cp_length * 0.8)
tmfilter = filter.fft_filter_fff(1, [1./cp_length]*cp_length)
self.connect( self.tm, tmfilter )
self.tm = tmfilter
self._pd_thres = 0.3
self._pd_lookahead = fft_length / 2 # empirically chosen
peak_detector = ofdm.peak_detector_02_fb(self._pd_lookahead, self._pd_thres)
self.connect(self.tm, peak_detector)
#log_to_file( self, peak_detector, "data/rec_peak_detector.char" )
frame_start = [0]*frame_length
frame_start[0] = 1
frame_start = self.frame_trigger_old = blocks.vector_source_b(frame_start,True)
delayed_timesync = blocks.delay(gr.sizeof_char,
(frame_length-1)*block_length + timingmetric_shift)
self.connect( peak_detector, delayed_timesync )
self.block_sampler = ofdm.vector_sampler(gr.sizeof_gr_complex,block_length*frame_length)
self.discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
self.connect(self.input,self.block_sampler)
self.connect(delayed_timesync,(self.block_sampler,1))
# TODO: dynamic solution
vt2s = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length,
frame_length)
self.connect(self.block_sampler,vt2s,self.discard_cp)
#terminate_stream(self,ofdm_blocks)
ofdm_blocks = self.discard_cp
# else:
# serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
# discard_cp = ofdm.vector_mask(block_length,cp_length,fft_length,[])
# ofdm_blocks = discard_cp
# self.connect( rx_input, serial_to_parallel, discard_cp )
# frame_start = [0]*frame_length
# frame_start[0] = 1
# frame_start = blocks.vector_source_b(frame_start,True)
#
# print "Disabled time synchronization stage"
## Compute autocorrelations for S&C preamble
## and cyclic prefix
#log_to_file( self, sc_metric, "data/sc_metric_ofdm.float" )
#log_to_file(self, frame_start, "data/frame_start.compl")
# log_to_file(self,ofdm_blocks,"data/ofdm_blocks_original.compl")
if options.disable_time_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, ofdm_blocks)
terminate_stream(self, frame_start)
serial_to_parallel = blocks.stream_to_vector(gr.sizeof_gr_complex,block_length)
discard_cp = ofdm.vector_mask_dc_null(block_length,cp_length,fft_length,dc_null, [])
ofdm_blocks = discard_cp
self.connect( rx_input, serial_to_parallel, discard_cp )
frame_start = [0]*frame_length
frame_start[0] = 1
frame_start = blocks.vector_source_b(frame_start,True)
print "Disabled time synchronization stage"
print"\t\t\t\t\tframe_length = ",frame_length
if options.ideal is False and options.ideal2 is False:
## Extract preamble, feed to Morelli & Mengali frequency offset estimator
assert( block_header.mm_preamble_pos == 0 )
morelli_foe = ofdm.mm_frequency_estimator( fft_length, L,1,0 )
sampler_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * fft_length,
1 )
self.connect( ofdm_blocks, ( sampler_preamble, 0 ) )
self.connect( frame_start, ( sampler_preamble, 1 ) )
self.connect( sampler_preamble, morelli_foe )
freq_offset = morelli_foe
## Adaptive LMS FIR filtering of frequency offset
lms_fir = ofdm.lms_fir_ff( 20, 1e-3 ) # TODO: verify parameter choice
self.connect( freq_offset, lms_fir )
freq_offset = lms_fir
#self.zmq_probe_freqoff = zeromq.pub_sink(gr.sizeof_float, 1, "tcp://*:5557")
self.connect(lms_fir, blocks.keep_one_in_n(gr.sizeof_float,20) ,out_disp_cfo)
else:
self.connect(blocks.vector_source_f ([1]) ,out_disp_cfo)
#log_to_file(self, lms_fir, "data/lms_fir.float")
if options.disable_freq_sync or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, freq_offset)
freq_offset = blocks.vector_source_f([0.0],True)
print "Disabled frequency synchronization stage"
if options.ideal is False and options.ideal2 is False:
## Correct frequency shift, feed-forward structure
frequency_shift = ofdm.frequency_shift_vcc( fft_length, -1.0/fft_length,
cp_length )
self.connect( ofdm_blocks, ( frequency_shift, 0 ) )
self.connect( freq_offset, ( frequency_shift, 1 ) )
self.connect( frame_start, ( frequency_shift, 2 ) )
ofdm_blocks = frequency_shift
## FFT
fft = fft_blocks.fft_vcc( fft_length, True, [], True )
self.connect( ofdm_blocks, fft )
ofdm_blocks = fft
#log_to_file( self, fft, "data/compen.float" )
## Remove virtual subcarriers
if fft_length > data_subc:
subcarrier_mask = ofdm.vector_mask_dc_null( fft_length, virtual_subc/2,
total_subc, dc_null, [] )
self.connect( ofdm_blocks, subcarrier_mask )
ofdm_blocks = subcarrier_mask
#log_to_file(self, ofdm_blocks, "data/vec_mask.compl")
## Least Squares estimator for channel transfer function (CTF)
if options.logcir:
log_to_file( self, ofdm_blocks, "data/OFDM_Blocks.compl" )
inv_preamble_fd = numpy.array( block_header.pilotsym_fd[
block_header.channel_estimation_pilot[0] ] )
inv_preamble_fd = numpy.concatenate([inv_preamble_fd[:total_subc/2],inv_preamble_fd[total_subc/2+dc_null:]])
#print "Channel estimation pilot: ", inv_preamble_fd
inv_preamble_fd = 1. / inv_preamble_fd
LS_channel_estimator0 = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
self.connect( ofdm_blocks, LS_channel_estimator0, gr.null_sink(gr.sizeof_gr_complex*total_subc))
log_to_file( self, LS_channel_estimator0, "data/OFDM_Blocks_eq.compl" )
## post-FFT processing
## extract channel estimation preamble from frame
if options.ideal is False and options.ideal2 is False:
chest_pre_trigger = blocks.delay( gr.sizeof_char, 1)
sampled_chest_preamble = ofdm.vector_sampler( gr.sizeof_gr_complex * total_subc, 1)
self.connect( frame_start, chest_pre_trigger )
self.connect( chest_pre_trigger, ( sampled_chest_preamble, 1 ) )
self.connect( ofdm_blocks, ( sampled_chest_preamble, 0 ) )
## Least Squares estimator for channel transfer function (CTF)
inv_preamble_fd = numpy.array( block_header.pilotsym_fd[
block_header.channel_estimation_pilot[0] ] )
inv_preamble_fd = numpy.concatenate([inv_preamble_fd[:total_subc/2],inv_preamble_fd[total_subc/2+dc_null:]])
#print "Channel estimation pilot: ", inv_preamble_fd
inv_preamble_fd = 1. / inv_preamble_fd
LS_channel_estimator = ofdm.multiply_const_vcc( list( inv_preamble_fd ) )
self.connect( sampled_chest_preamble, LS_channel_estimator )
estimated_CTF = LS_channel_estimator
if options.logcir:
log_to_file( self, sampled_chest_preamble, "data/PREAM.compl" )
if not options.disable_ctf_enhancer:
if options.logcir:
ifft1 = fft_blocks.fft_vcc(total_subc,False,[],True)
self.connect( estimated_CTF, ifft1,gr.null_sink(gr.sizeof_gr_complex*total_subc))
summ1 = ofdm.vector_sum_vcc(total_subc)
c2m =gr.complex_to_mag(total_subc)
self.connect( estimated_CTF,summ1 ,gr.null_sink(gr.sizeof_gr_complex))
self.connect( estimated_CTF, c2m,gr.null_sink(gr.sizeof_float*total_subc))
log_to_file( self, ifft1, "data/CIR1.compl" )
log_to_file( self, summ1, "data/CTFsumm1.compl" )
log_to_file( self, estimated_CTF, "data/CTF1.compl" )
log_to_file( self, c2m, "data/CTFmag1.float" )
## MSE enhancer
ctf_mse_enhancer = ofdm.CTF_MSE_enhancer( total_subc, cp_length + cp_length)
self.connect( estimated_CTF, ctf_mse_enhancer )
# log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer_original.compl")
#ifft3 = fft_blocks.fft_vcc(total_subc,False,[],True)
#null_noise = ofdm.noise_nulling(total_subc, cp_length + cp_length)
#ctf_mse_enhancer = fft_blocks.fft_vcc(total_subc,True,[],True)
#ctf_mse_enhancer = ofdm.vector_mask( fft_length, virtual_subc/2,
# total_subc, [] )
#self.connect( estimated_CTF, ifft3,null_noise,ctf_mse_enhancer )
estimated_CTF = ctf_mse_enhancer
print "Disabled CTF MSE enhancer"
if options.logcir:
ifft2 = fft_blocks.fft_vcc(total_subc,False,[],True)
self.connect( estimated_CTF, ifft2,gr.null_sink(gr.sizeof_gr_complex*total_subc))
summ2 = ofdm.vector_sum_vcc(total_subc)
c2m2 =gr.complex_to_mag(total_subc)
self.connect( estimated_CTF,summ2 ,gr.null_sink(gr.sizeof_gr_complex))
self.connect( estimated_CTF, c2m2,gr.null_sink(gr.sizeof_float*total_subc))
log_to_file( self, ifft2, "data/CIR2.compl" )
log_to_file( self, summ2, "data/CTFsumm2.compl" )
log_to_file( self, estimated_CTF, "data/CTF2.compl" )
log_to_file( self, c2m2, "data/CTFmag2.float" )
## Postprocess the CTF estimate
## CTF -> inverse CTF (for equalizer)
## CTF -> norm |.|^2 (for CTF display)
ctf_postprocess = ofdm.postprocess_CTF_estimate( total_subc )
self.connect( estimated_CTF, ctf_postprocess )
inv_estimated_CTF = ( ctf_postprocess, 0 )
disp_CTF = ( ctf_postprocess, 1 )
# if options.disable_equalization or options.ideal:
# terminate_stream(self, inv_estimated_CTF)
# inv_estimated_CTF_vec = blocks.vector_source_c([1.0/fft_length*math.sqrt(total_subc)]*total_subc,True,total_subc)
# inv_estimated_CTF_str = blocks.vector_to_stream(gr.sizeof_gr_complex, total_subc)
# self.inv_estimated_CTF_mul = ofdm.multiply_const_ccf( 1.0/config.rms_amplitude )
# #inv_estimated_CTF_mul.set_k(1.0/config.rms_amplitude)
# inv_estimated_CTF = blocks.stream_to_vector(gr.sizeof_gr_complex, total_subc)
# self.connect( inv_estimated_CTF_vec, inv_estimated_CTF_str, self.inv_estimated_CTF_mul, inv_estimated_CTF)
# print "Disabled equalization stage"
'''
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print"\t\t\t\t\tnondata_blocks=",nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking = ofdm.lms_phase_tracking_03( total_subc, pilot_subc,
nondata_blocks, pilot_subcarriers,0 )
self.connect( ofdm_blocks, ( phase_tracking, 0 ) )
self.connect( inv_estimated_CTF, ( phase_tracking, 1 ) )
self.connect( frame_start, ( phase_tracking, 2 ) ) ##
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
if options.disable_phase_tracking or options.ideal:
terminate_stream(self, phase_tracking)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking
'''
## Channel Equalizer
if options.disable_equalization or options.ideal or options.ideal2:
print "Disabled equalization stage"
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, inv_estimated_CTF)
else:
equalizer = ofdm.channel_equalizer( total_subc )
self.connect( ofdm_blocks, ( equalizer, 0 ) )
self.connect( inv_estimated_CTF, ( equalizer, 1 ) )
self.connect( frame_start, ( equalizer, 2 ) )
ofdm_blocks = equalizer
#log_to_file(self, equalizer,"data/equalizer_siso.compl")
#log_to_file(self, ofdm_blocks, "data/equalizer.compl")
## LMS Phase tracking
## Track residual frequency offset and sampling clock frequency offset
if options.ideal is False and options.ideal2 is False:
nondata_blocks = []
for i in range(config.frame_length):
if i in config.training_data.pilotsym_pos:
nondata_blocks.append(i)
print"\t\t\t\t\tnondata_blocks=",nondata_blocks
pilot_subc = block_header.pilot_tones
pilot_subcarriers = block_header.pilot_subc_sym
print "PILOT SUBCARRIERS: ", pilot_subcarriers
phase_tracking2 = ofdm.lms_phase_tracking_dc_null( total_subc, pilot_subc,
nondata_blocks, pilot_subcarriers, dc_null )
self.connect( ofdm_blocks, ( phase_tracking2, 0 ) )
self.connect( frame_start, ( phase_tracking2, 1 ) ) ##
if options.disable_phase_tracking or options.ideal or options.ideal2:
if options.ideal is False and options.ideal2 is False:
terminate_stream(self, phase_tracking2)
print "Disabled phase tracking stage"
else:
ofdm_blocks = phase_tracking2
if options.scatter_plot_before_phase_tracking:
self.before_phase_tracking = equalizer
## Output connections
self.connect( ofdm_blocks, out_ofdm_blocks )
self.connect( frame_start, out_frame_start )
if options.ideal is False and options.ideal2 is False:
self.connect( disp_CTF, out_disp_ctf )
else:
self.connect( blocks.vector_source_f([1.0]*total_subc),blocks.stream_to_vector(gr.sizeof_float,total_subc), out_disp_ctf )
if log:
log_to_file( self, sc_metric, "data/sc_metric.float" )
log_to_file( self, gi_metric, "data/gi_metric.float" )
log_to_file( self, morelli_foe, "data/morelli_foe.float" )
log_to_file( self, lms_fir, "data/lms_fir.float" )
log_to_file( self, sampler_preamble, "data/preamble.compl" )
log_to_file( self, sync, "data/sync.compl" )
log_to_file( self, frequency_shift, "data/frequency_shift.compl" )
log_to_file( self, fft, "data/fft.compl")
log_to_file( self, fft, "data/fft.float", mag=True )
if vars().has_key( 'subcarrier_mask' ):
log_to_file( self, subcarrier_mask, "data/subcarrier_mask.compl" )
log_to_file( self, ofdm_blocks, "data/ofdm_blocks_out.compl" )
log_to_file( self, frame_start, "data/frame_start.float",
char_to_float=True )
log_to_file( self, sampled_chest_preamble,
"data/sampled_chest_preamble.compl" )
log_to_file( self, LS_channel_estimator,
"data/ls_channel_estimator.compl" )
log_to_file( self, LS_channel_estimator,
"data/ls_channel_estimator.float", mag=True )
if "ctf_mse_enhancer" in locals():
log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.compl" )
log_to_file( self, ctf_mse_enhancer, "data/ctf_mse_enhancer.float",
mag=True )
log_to_file( self, (ctf_postprocess,0), "data/inc_estimated_ctf.compl" )
log_to_file( self, (ctf_postprocess,1), "data/disp_ctf.float" )
log_to_file( self, equalizer, "data/equalizer.compl" )
log_to_file( self, equalizer, "data/equalizer.float", mag=True )
log_to_file( self, phase_tracking, "data/phase_tracking.compl" )
def __init__(self, fft_length, block_length, frame_data_part, block_header,
options):
gr.hier_block2.__init__(self, "ofdm_receiver",
gr.io_signature (1,1,gr.sizeof_gr_complex),
gr.io_signature2(2,2,gr.sizeof_gr_complex*fft_length,
gr.sizeof_char))
frame_length = frame_data_part + block_header.no_pilotsyms
cp_length = block_length-fft_length
self.input=gr.kludge_copy(gr.sizeof_gr_complex)
self.connect(self, self.input)
self.blocks_out = (self,0)
self.frame_trigger_out = (self,1)
self.snr_out = (self,2)
if options.log:
log_to_file(self, self.input, "data/receiver_input.compl")
# peak detector: thresholds low, high
#self._pd_thres_lo = 0.09
#self._pd_thres_hi = 0.1
self._pd_thres = 0.2
self._pd_lookahead = fft_length / 2 # empirically chosen
#########################
# coarse timing offset estimator
# self.tm = schmidl.modified_timing_metric(fft_length,[1]*(fft_length))
self.tm = schmidl.recursive_timing_metric(fft_length)
self.connect(self.input,self.tm)
assert(hasattr(block_header, 'sc_preamble_pos'))
assert(block_header.sc_preamble_pos == 0) # TODO: relax this restriction
if options.filter_timingmetric:
timingmetric_shift = -2 #int(-cp_length * 0.8)
tmfilter = gr.fir_filter_fff(1, [1./cp_length]*cp_length)
self.connect( self.tm, tmfilter )
self.timing_metric = tmfilter
print "Filtering timing metric, experimental"
else:
self.timing_metric = self.tm
timingmetric_shift = int(-cp_length/4)
if options.log:
log_to_file(self, self.timing_metric, "data/tm.float")
# peak detection
#threshold = gr.threshold_ff(self._pd_thres_lo,self._pd_thres_hi,0)
#muted_tm = gr.multiply_ff()
peak_detector = peak_detector_02_fb(self._pd_lookahead, self._pd_thres)
#self.connect(self.timing_metric, threshold, (muted_tm,0))
#self.connect(self.timing_metric, (muted_tm,1))
#self.connect(muted_tm, peak_detector)
self.connect(self.timing_metric, peak_detector)
if options.log:
pd_float = gr.char_to_float()
self.connect(peak_detector,pd_float)
log_to_file(self, pd_float, "data/peakdetector.float")
if options.no_timesync:
terminate_stream( self, peak_detector )
trigger = [0]*(frame_length*block_length)
trigger[ block_length-1 ] = 1
peak_detector = blocks.vector_source_b( trigger, True )
print "Bypassing timing synchronisation"
# TODO: refine detected peaks with 90% average method as proposed
# from Schmidl & Cox:
# Starting from peak, find first points to the left and right whose
# value is less than or equal 90% of the peak value. New trigger point
# is average of both
# Frequency Offset Estimation
# Used: Algorithm as proposed from Morelli & Mengali
# Idea: Use periodic preamble, correlate identical parts, determine
# phase offset. This phase offset is a function of the frequency offset.
assert(hasattr(block_header, 'mm_preamble_pos'))
foe = morelli_foe(fft_length,block_header.mm_periodic_parts)
self.connect(self.input,(foe,0))
if block_header.mm_preamble_pos > 0:
delayed_trigger = gr.delay(gr.sizeof_char,
block_header.mm_preamble_pos*block_length)
self.connect(peak_detector,delayed_trigger,(foe,1))
else:
self.connect(peak_detector,(foe,1))
self.freq_offset = foe
if options.log:
log_to_file(self, self.freq_offset, "data/freqoff_out.float")
if options.average_freqoff:
#avg_foe = gr.single_pole_iir_filter_ff( 0.1 )
avg_foe = ofdm.lms_fir_ff( 20, 1e-3 )
self.connect( self.freq_offset, avg_foe )
self.freq_offset = avg_foe
#log_to_file( self, avg_foe, "data/freqoff_out_avg.float" )
print "EXPERIMENTAL!!! Filtering frequency offset estimate"
if options.no_freqsync:
terminate_stream( self, self.freq_offset )
self.freq_offset = blocks.vector_source_f( [0.0], True )
print "Bypassing frequency offset estimator, offset=0.0"
# TODO: dynamic solution
frametrig_seq = concatenate([[1],[0]*(frame_length-1)])
self.time_sync = peak_detector
self.frame_trigger = blocks.vector_source_b(frametrig_seq,True)
self.connect(self.frame_trigger, self.frame_trigger_out)
##########################
# symbol extraction and processing
# First, we extract the whole ofdm block, then we divide this block into
# several ofdm symbols. This asserts that all symbols belonging to the
# same ofdm block will be a consecutive order.
# extract ofdm symbols
# compensate frequency offset
# TODO: use PLL and update/reset signals
delayed_timesync = gr.delay(gr.sizeof_char,
(frame_length-1)*block_length+timingmetric_shift)
self.connect( self.time_sync, delayed_timesync )
self.block_sampler = vector_sampler(gr.sizeof_gr_complex,block_length*frame_length)
self.discard_cp = vector_mask(block_length,cp_length,fft_length,[])
if options.use_dpll:
dpll = gr.dpll_bb( frame_length * block_length , .01 )
self.connect( delayed_timesync, dpll )
if options.log:
dpll_f = gr.char_to_float()
delayed_timesync_f = gr.char_to_float()
self.connect( dpll, dpll_f )
self.connect( delayed_timesync, delayed_timesync_f )
log_to_file( self, dpll_f, "data/dpll.float" )
log_to_file( self, delayed_timesync_f, "data/dpll_in.float" )
delayed_timesync = dpll
print "Using DPLL, EXPERIMENTAL!!!!!"
self.connect(self.input,self.block_sampler)
self.connect(delayed_timesync,(self.block_sampler,1))
if options.log:
log_to_file(self, self.block_sampler, "data/block_sampler_out.compl")
# TODO: dynamic solution
self.ofdm_symbols = blocks.vector_to_stream(gr.sizeof_gr_complex*block_length,
frame_length)
self.connect(self.block_sampler,self.ofdm_symbols,self.discard_cp)
if options.log:
log_to_file(self, self.discard_cp, "data/discard_cp_out.compl")
dcp_fft = gr.fft_vcc(fft_length, True, [], True)
self.connect(self.discard_cp,dcp_fft)
log_to_file(self, dcp_fft, "data/discard_cp_fft.compl")
# reset phase accumulator inside freq_shift on every block start
# setup output connection
freq_shift = frequency_shift_vcc(fft_length, -1.0/fft_length, cp_length)
self.connect(self.discard_cp,(freq_shift,0))
self.connect(self.freq_offset,(freq_shift,1))
self.connect(self.frame_trigger,(freq_shift,2))
self.connect(freq_shift, self.blocks_out)
if options.log:
log_to_file(self, freq_shift, "data/freqshift_out.compl")
if options.no_freqshift:
terminate_stream( self, freq_shift )
freq_shift = self.discard_cp
print "Bypassing frequency shift block"
