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, 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 test_vff_001(self):
N = 10
data = [2.0] * N
src = gr.vector_source_c(data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, N)
dst = gr.vector_sink_c()
uut = ofdm.vector_sum_vcc(N)
self.fg.connect(src, s2v, uut, dst)
self.fg.run()
self.assertEqual([sum(data)], list(dst.data()))
def test_vcc_002(self):
N = 10
data = [1.0 + 2.0j] * (N * 2)
src = gr.vector_source_c(data)
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, N)
dst = gr.vector_sink_c()
uut = ofdm.vector_sum_vcc(N)
self.fg.connect(src, s2v, uut, dst)
self.fg.run()
self.assertEqual([sum(data[0:N]), sum(data[N:2 * N])],
list(dst.data()))
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):
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
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, 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, 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" )