def __init__(self, audio_rate):
gr.hier_block2.__init__(
self,
"standard_squelch",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193, 0, -0.0193),
(1, 1.9524, -0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(
1 / (0.01 * audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193, 0, -0.0193),
(1, 1.3597, -0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1 / (0.01 * audio_rate))
self.sub = gr.sub_ff()
self.add = gr.add_ff()
self.gate = gr.threshold_ff(0.3, 0.43, 0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1 /
(0.01 * audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
self.connect(self, self.input_node)
self.connect(self.input_node, (self.squelch_mult, 0))
self.connect(self.input_node, self.low_iir)
self.connect(self.low_iir, (self.low_square, 0))
self.connect(self.low_iir, (self.low_square, 1))
self.connect(self.low_square, self.low_smooth, (self.sub, 0))
self.connect(self.low_smooth, (self.add, 0))
self.connect(self.input_node, self.hi_iir)
self.connect(self.hi_iir, (self.hi_square, 0))
self.connect(self.hi_iir, (self.hi_square, 1))
self.connect(self.hi_square, self.hi_smooth, (self.sub, 1))
self.connect(self.hi_smooth, (self.add, 1))
self.connect(self.sub, (self.div, 0))
self.connect(self.add, (self.div, 1))
self.connect(self.div, self.gate, self.squelch_lpf,
(self.squelch_mult, 1))
self.connect(self.squelch_mult, self)
def __init__(self, audio_rate):
gr.hier_block2.__init__(self, "standard_squelch",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.9524,-0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.3597,-0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.sub = gr.sub_ff();
self.add = gr.add_ff();
self.gate = gr.threshold_ff(0.3,0.43,0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
self.connect (self, self.input_node)
self.connect (self.input_node, (self.squelch_mult, 0))
self.connect (self.input_node,self.low_iir)
self.connect (self.low_iir,(self.low_square,0))
self.connect (self.low_iir,(self.low_square,1))
self.connect (self.low_square,self.low_smooth,(self.sub,0))
self.connect (self.low_smooth, (self.add,0))
self.connect (self.input_node,self.hi_iir)
self.connect (self.hi_iir,(self.hi_square,0))
self.connect (self.hi_iir,(self.hi_square,1))
self.connect (self.hi_square,self.hi_smooth,(self.sub,1))
self.connect (self.hi_smooth, (self.add,1))
self.connect (self.sub, (self.div, 0))
self.connect (self.add, (self.div, 1))
self.connect (self.div, self.gate, self.squelch_lpf, (self.squelch_mult,1))
self.connect (self.squelch_mult, self)
def __init__(self, fg, audio_rate):
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.9524,-0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.3597,-0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.sub = gr.sub_ff();
self.add = gr.add_ff();
self.gate = gr.threshold_ff(0.3,0.43,0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
fg.connect (self.input_node, (self.squelch_mult, 0))
fg.connect (self.input_node,self.low_iir)
fg.connect (self.low_iir,(self.low_square,0))
fg.connect (self.low_iir,(self.low_square,1))
fg.connect (self.low_square,self.low_smooth,(self.sub,0))
fg.connect (self.low_smooth, (self.add,0))
fg.connect (self.input_node,self.hi_iir)
fg.connect (self.hi_iir,(self.hi_square,0))
fg.connect (self.hi_iir,(self.hi_square,1))
fg.connect (self.hi_square,self.hi_smooth,(self.sub,1))
fg.connect (self.hi_smooth, (self.add,1))
fg.connect (self.sub, (self.div, 0))
fg.connect (self.add, (self.div, 1))
fg.connect (self.div, self.gate, self.squelch_lpf, (self.squelch_mult,1))
gr.hier_block.__init__(self, fg, self.input_node, self.squelch_mult)
def __init__(
self,
agc_max=100,
agc_decay=0.1,
freq_offset=1000000,
outfile="datafifo",
bandpass_bandwidth=20,
threshold_buffer=0.25,
threshold_center=0.5,
agc_attack=0.1,
bandpass_transition_width=1000000,
):
gr.top_block.__init__(self, "Collect")
##################################################
# Parameters
##################################################
self.agc_max = agc_max
self.agc_decay = agc_decay
self.freq_offset = freq_offset
self.outfile = outfile
self.bandpass_bandwidth = bandpass_bandwidth
self.threshold_buffer = threshold_buffer
self.threshold_center = threshold_center
self.agc_attack = agc_attack
self.bandpass_transition_width = bandpass_transition_width
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 64000000
##################################################
# Blocks
##################################################
self.uhd_usrp_source_0 = uhd.usrp_source(device_addr="", io_type=uhd.io_type.COMPLEX_FLOAT32, num_channels=1)
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(915000000 - freq_offset, 0)
self.uhd_usrp_source_0.set_gain(0, 0)
self.uhd_usrp_source_0.set_antenna("TX/RX", 0)
self.gr_threshold_ff_0 = gr.threshold_ff(
threshold_center - threshold_buffer, threshold_center + threshold_buffer, 0
)
self.gr_map_bb_0 = gr.map_bb(([48, 49]))
self.gr_float_to_char_0 = gr.float_to_char()
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char * 1, outfile)
self.gr_file_sink_0.set_unbuffered(False)
self.gr_complex_to_mag_0 = gr.complex_to_mag(1)
self.gr_agc2_xx_0_0 = gr.agc2_cc(agc_attack, agc_decay, 1.0, 1.0, agc_max)
self.band_pass_filter_0 = gr.fir_filter_ccf(
1,
firdes.band_pass(
1,
samp_rate,
freq_offset - bandpass_bandwidth / 2,
freq_offset + bandpass_bandwidth / 2,
bandpass_transition_width,
firdes.WIN_HAMMING,
6.76,
),
)
##################################################
# Connections
##################################################
self.connect((self.gr_float_to_char_0, 0), (self.gr_map_bb_0, 0))
self.connect((self.gr_map_bb_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.gr_agc2_xx_0_0, 0))
self.connect((self.gr_agc2_xx_0_0, 0), (self.band_pass_filter_0, 0))
self.connect((self.gr_threshold_ff_0, 0), (self.gr_float_to_char_0, 0))
self.connect((self.gr_complex_to_mag_0, 0), (self.gr_threshold_ff_0, 0))
self.connect((self.band_pass_filter_0, 0), (self.gr_complex_to_mag_0, 0))
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, 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, cp_length, snr, kstime, logging):
''' Maximum Likelihood OFDM synchronizer:
J. van de Beek, M. Sandell, and P. O. Borjesson, "ML Estimation
of Time and Frequency Offset in OFDM Systems," IEEE Trans.
Signal Processing, vol. 45, no. 7, pp. 1800-1805, 1997.
'''
gr.hier_block2.__init__(self, "ofdm_sync_ml",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
SNR = 10.0**(snr/10.0)
rho = SNR / (SNR + 1.0)
symbol_length = fft_length + cp_length
# ML Sync
# Energy Detection from ML Sync
self.connect(self, self.input)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length)
self.connect(self.input, self.delay)
# magnitude squared blocks
self.magsqrd1 = gr.complex_to_mag_squared()
self.magsqrd2 = gr.complex_to_mag_squared()
self.adder = gr.add_ff()
moving_sum_taps = [rho/2 for i in range(cp_length)]
self.moving_sum_filter = gr.fir_filter_fff(1,moving_sum_taps)
self.connect(self.input,self.magsqrd1)
self.connect(self.delay,self.magsqrd2)
self.connect(self.magsqrd1,(self.adder,0))
self.connect(self.magsqrd2,(self.adder,1))
self.connect(self.adder,self.moving_sum_filter)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.mixer = gr.multiply_cc();
movingsum2_taps = [1.0 for i in range(cp_length)]
self.movingsum2 = gr.fir_filter_ccf(1,movingsum2_taps)
# Correlator data handler
self.c2mag = gr.complex_to_mag()
self.angle = gr.complex_to_arg()
self.connect(self.input,(self.mixer,1))
self.connect(self.delay,self.conjg,(self.mixer,0))
self.connect(self.mixer,self.movingsum2,self.c2mag)
self.connect(self.movingsum2,self.angle)
# ML Sync output arg, need to find maximum point of this
self.diff = gr.sub_ff()
self.connect(self.c2mag,(self.diff,0))
self.connect(self.moving_sum_filter,(self.diff,1))
#ML measurements input to sampler block and detect
self.f2c = gr.float_to_complex()
self.pk_detect = gr.peak_detector_fb(0.2, 0.25, 30, 0.0005)
self.sample_and_hold = gr.sample_and_hold_ff()
# use the sync loop values to set the sampler and the NCO
# self.diff = theta
# self.angle = epsilon
self.connect(self.diff, self.pk_detect)
# The DPLL corrects for timing differences between CP correlations
use_dpll = 0
if use_dpll:
self.dpll = gr.dpll_bb(float(symbol_length),0.01)
self.connect(self.pk_detect, self.dpll)
self.connect(self.dpll, (self.sample_and_hold,1))
else:
self.connect(self.pk_detect, (self.sample_and_hold,1))
self.connect(self.angle, (self.sample_and_hold,0))
################################
# correlate against known symbol
# This gives us the same timing signal as the PN sync block only on the preamble
# we don't use the signal generated from the CP correlation because we don't want
# to readjust the timing in the middle of the packet or we ruin the equalizer settings.
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.kscorr = gr.fir_filter_ccc(1, kstime)
self.corrmag = gr.complex_to_mag_squared()
self.div = gr.divide_ff()
# The output signature of the correlation has a few spikes because the rest of the
# system uses the repeated preamble symbol. It needs to work that generically if
# anyone wants to use this against a WiMAX-like signal since it, too, repeats.
# The output theta of the correlator above is multiplied with this correlation to
# identify the proper peak and remove other products in this cross-correlation
self.threshold_factor = 0.1
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0)
self.f2b = gr.float_to_char()
self.b2f = gr.char_to_float()
self.mul = gr.multiply_ff()
# Normalize the power of the corr output by the energy. This is not really needed
# and could be removed for performance, but it makes for a cleaner signal.
# if this is removed, the threshold value needs adjustment.
self.connect(self.input, self.kscorr, self.corrmag, (self.div,0))
self.connect(self.moving_sum_filter, (self.div,1))
self.connect(self.div, (self.mul,0))
self.connect(self.pk_detect, self.b2f, (self.mul,1))
self.connect(self.mul, self.slice)
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.slice, self.f2b, (self,1))
if logging:
self.connect(self.moving_sum_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-energy_f.dat"))
self.connect(self.diff, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-epsilon_f.dat"))
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-corrmag_f.dat"))
self.connect(self.kscorr, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-kscorr_c.dat"))
self.connect(self.div, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-div_f.dat"))
self.connect(self.mul, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-mul_f.dat"))
self.connect(self.slice, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-slice_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-peaks_b.dat"))
if use_dpll:
self.connect(self.dpll, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-dpll_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-input_c.dat"))
def __init__(self, fft_length, cp_length, kstime, logging=False):
"""
OFDM synchronization using PN Correlation and initial cross-correlation:
F. Tufvesson, O. Edfors, and M. Faulkner, "Time and Frequency Synchronization for OFDM using
PN-Sequency Preambles," IEEE Proc. VTC, 1999, pp. 2203-2207.
This implementation is meant to be a more robust version of the Schmidl and Cox receiver design.
By correlating against the preamble and using that as the input to the time-delayed correlation,
this circuit produces a very clean timing signal at the end of the preamble. The timing is
more accurate and does not have the problem associated with determining the timing from the
plateau structure in the Schmidl and Cox.
This implementation appears to require that the signal is received with a normalized power or signal
scalling factor to reduce ambiguities intorduced from partial correlation of the cyclic prefix and
the peak detection. A better peak detection block might fix this.
Also, the cross-correlation falls apart as the frequency offset gets larger and completely fails
when an integer offset is introduced. Another thing to look at.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pnac",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
symbol_length = fft_length + cp_length
# PN Sync with cross-correlation input
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime[0:fft_length//2]]
kstime.reverse()
self.crosscorr_filter = filter.fir_filter_ccc(1, kstime)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the input
self.mag = gr.complex_to_mag_squared()
movingsum_taps = (fft_length//1)*[1.0,]
self.power = filter.fir_filter_fff(1,movingsum_taps)
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.compare = gr.sub_ff()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.threshold = gr.threshold_ff(0,0,0) # threshold detection might need to be tweaked
self.peaks = gr.float_to_char()
self.connect(self, self.input)
# Cross-correlate input signal with known preamble
self.connect(self.input, self.crosscorr_filter)
# use the output of the cross-correlation as input time-shifted correlation
self.connect(self.crosscorr_filter, self.delay)
self.connect(self.crosscorr_filter, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.c2mag)
self.connect(self.corr, self.angle)
self.connect(self.angle, (self.sample_and_hold,0))
# Get the power of the input signal to compare against the correlation
self.connect(self.crosscorr_filter, self.mag, self.power)
# Compare the power to the correlator output to determine timing peak
# When the peak occurs, it peaks above zero, so the thresholder detects this
self.connect(self.c2mag, (self.compare,0))
self.connect(self.power, (self.compare,1))
self.connect(self.compare, self.threshold)
self.connect(self.threshold, self.peaks, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.peaks, (self,1))
if logging:
self.connect(self.compare, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-compare_f.dat"))
self.connect(self.c2mag, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-theta_f.dat"))
self.connect(self.power, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-inputpower_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-epsilon_f.dat"))
self.connect(self.threshold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-threshold_f.dat"))
self.connect(self.peaks, gr.file_sink(gr.sizeof_char, "ofdm_sync_pnac-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pnac-input_c.dat"))
def __init__(self,
agc_max=100,
agc_decay=0.1,
freq_offset=1000000,
outfile="datafifo",
bandpass_bandwidth=20,
threshold_buffer=0.25,
threshold_center=0.5,
agc_attack=0.1,
bandpass_transition_width=1000000):
gr.top_block.__init__(self, "Collect")
##################################################
# Parameters
##################################################
self.agc_max = agc_max
self.agc_decay = agc_decay
self.freq_offset = freq_offset
self.outfile = outfile
self.bandpass_bandwidth = bandpass_bandwidth
self.threshold_buffer = threshold_buffer
self.threshold_center = threshold_center
self.agc_attack = agc_attack
self.bandpass_transition_width = bandpass_transition_width
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 64000000
##################################################
# Blocks
##################################################
self.uhd_usrp_source_0 = uhd.usrp_source(
device_addr="",
io_type=uhd.io_type.COMPLEX_FLOAT32,
num_channels=1,
)
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(915000000 - freq_offset, 0)
self.uhd_usrp_source_0.set_gain(0, 0)
self.uhd_usrp_source_0.set_antenna("TX/RX", 0)
self.gr_threshold_ff_0 = gr.threshold_ff(
threshold_center - threshold_buffer,
threshold_center + threshold_buffer, 0)
self.gr_map_bb_0 = gr.map_bb(([48, 49]))
self.gr_float_to_char_0 = gr.float_to_char()
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char * 1, outfile)
self.gr_file_sink_0.set_unbuffered(False)
self.gr_complex_to_mag_0 = gr.complex_to_mag(1)
self.gr_agc2_xx_0_0 = gr.agc2_cc(agc_attack, agc_decay, 1.0, 1.0,
agc_max)
self.band_pass_filter_0 = gr.fir_filter_ccf(
1,
firdes.band_pass(1, samp_rate,
freq_offset - bandpass_bandwidth / 2,
freq_offset + bandpass_bandwidth / 2,
bandpass_transition_width, firdes.WIN_HAMMING,
6.76))
##################################################
# Connections
##################################################
self.connect((self.gr_float_to_char_0, 0), (self.gr_map_bb_0, 0))
self.connect((self.gr_map_bb_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.uhd_usrp_source_0, 0), (self.gr_agc2_xx_0_0, 0))
self.connect((self.gr_agc2_xx_0_0, 0), (self.band_pass_filter_0, 0))
self.connect((self.gr_threshold_ff_0, 0), (self.gr_float_to_char_0, 0))
self.connect((self.gr_complex_to_mag_0, 0),
(self.gr_threshold_ff_0, 0))
self.connect((self.band_pass_filter_0, 0),
(self.gr_complex_to_mag_0, 0))
def __init__(self, fft_length, cp_length, kstime, logging=False):
"""
OFDM synchronization using PN Correlation and initial cross-correlation:
F. Tufvesson, O. Edfors, and M. Faulkner, "Time and Frequency Synchronization for OFDM using
PN-Sequency Preambles," IEEE Proc. VTC, 1999, pp. 2203-2207.
This implementation is meant to be a more robust version of the Schmidl and Cox receiver design.
By correlating against the preamble and using that as the input to the time-delayed correlation,
this circuit produces a very clean timing signal at the end of the preamble. The timing is
more accurate and does not have the problem associated with determining the timing from the
plateau structure in the Schmidl and Cox.
This implementation appears to require that the signal is received with a normalized power or signal
scalling factor to reduce ambiguities intorduced from partial correlation of the cyclic prefix and
the peak detection. A better peak detection block might fix this.
Also, the cross-correlation falls apart as the frequency offset gets larger and completely fails
when an integer offset is introduced. Another thing to look at.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pnac",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
symbol_length = fft_length + cp_length
# PN Sync with cross-correlation input
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime[0:fft_length // 2]]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length / 2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc()
self.corr = gr.multiply_cc()
# Create a moving sum filter for the input
self.mag = gr.complex_to_mag_squared()
movingsum_taps = (fft_length // 1) * [
1.0,
]
self.power = gr.fir_filter_fff(1, movingsum_taps)
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.compare = gr.sub_ff()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.threshold = gr.threshold_ff(
0, 0, 0) # threshold detection might need to be tweaked
self.peaks = gr.float_to_char()
self.connect(self, self.input)
# Cross-correlate input signal with known preamble
self.connect(self.input, self.crosscorr_filter)
# use the output of the cross-correlation as input time-shifted correlation
self.connect(self.crosscorr_filter, self.delay)
self.connect(self.crosscorr_filter, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.c2mag)
self.connect(self.corr, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0))
# Get the power of the input signal to compare against the correlation
self.connect(self.crosscorr_filter, self.mag, self.power)
# Compare the power to the correlator output to determine timing peak
# When the peak occurs, it peaks above zero, so the thresholder detects this
self.connect(self.c2mag, (self.compare, 0))
self.connect(self.power, (self.compare, 1))
self.connect(self.compare, self.threshold)
self.connect(self.threshold, self.peaks, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
self.connect(self.peaks, (self, 1))
if logging:
self.connect(
self.compare,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-compare_f.dat"))
self.connect(
self.c2mag,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-theta_f.dat"))
self.connect(
self.power,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pnac-inputpower_f.dat"))
self.connect(
self.angle,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pnac-epsilon_f.dat"))
self.connect(
self.threshold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pnac-threshold_f.dat"))
self.connect(
self.peaks,
gr.file_sink(gr.sizeof_char, "ofdm_sync_pnac-peaks_b.dat"))
self.connect(
self.sample_and_hold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pnac-sample_and_hold_f.dat"))
self.connect(
self.input,
gr.file_sink(gr.sizeof_gr_complex,
"ofdm_sync_pnac-input_c.dat"))
def __init__(self, fft_length, cp_length, kstime, threshold, threshold_type, threshold_gap, logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(self, "ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.corr = gr.multiply_cc();
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length//2)]
self.moving_sum_filter = gr.fir_filter_ccf(1,moving_sum_taps)
else:
moving_sum_taps = [complex(1.0,0.0) for i in range(fft_length//2)]
self.moving_sum_filter = gr.fft_filter_ccc(1,moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length//2)]
#movingsum2_taps = [0.5 for i in range(fft_length*4)] #apurv - implementing Veljo's suggestion, when pause b/w packets
if 1:
self.inputmovingsum = gr.fir_filter_fff(1,movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1,movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001) #apurv - implementing Veljo's suggestion, when pause b/w packets
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr,0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr,1))
self.connect(self.corr, self.moving_sum_filter)
#self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold,0)) # apurv--
#self.connect(self.angle, gr.delay(gr.sizeof_float, offset), (self.sample_and_hold, 0)) #apurv++
cross_correlate = 1
if cross_correlate==1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# get the magnitude #
self.corrmag = gr.complex_to_mag_squared()
self.f2b = gr.float_to_char()
self.threshold_factor = threshold #0.0012 #0.012 #0.0015
if 0:
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0, fft_length)
else:
#thresholds = [self.threshold_factor, 9e-5]
self.slice = gr.threshold_ff(threshold, threshold, 0, fft_length, threshold_type, threshold_gap)
self.connect(self.input, self.crosscorr_filter, self.corrmag, self.slice, self.f2b)
# some debug dump #
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
#self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
self.connect(self.f2b, (self.sample_and_hold,1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
#self.connect(self.pk_detect, (self,1)) #removed
#self.connect(self.f2b, gr.delay(gr.sizeof_char, 1), (self, 1))
self.connect(self.f2b, (self, 1))
if logging:
self.connect(self.matched_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(self.normalize, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
def __init__(self,
fft_length,
cp_length,
kstime,
threshold,
threshold_type,
threshold_gap,
logging=False):
"""
OFDM synchronization using PN Correlation:
T. M. Schmidl and D. C. Cox, "Robust Frequency and Timing
Synchonization for OFDM," IEEE Trans. Communications, vol. 45,
no. 12, 1997.
"""
gr.hier_block2.__init__(
self,
"ofdm_sync_pn",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float,
gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length / 2)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc()
self.corr = gr.multiply_cc()
# Create a moving sum filter for the corr output
if 1:
moving_sum_taps = [1.0 for i in range(fft_length // 2)]
self.moving_sum_filter = gr.fir_filter_ccf(1, moving_sum_taps)
else:
moving_sum_taps = [
complex(1.0, 0.0) for i in range(fft_length // 2)
]
self.moving_sum_filter = gr.fft_filter_ccc(1, moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = gr.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length // 2)]
#movingsum2_taps = [0.5 for i in range(fft_length*4)] #apurv - implementing Veljo's suggestion, when pause b/w packets
if 1:
self.inputmovingsum = gr.fir_filter_fff(1, movingsum2_taps)
else:
self.inputmovingsum = gr.fft_filter_fff(1, movingsum2_taps)
self.square = gr.multiply_ff()
self.normalize = gr.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = gr.complex_to_mag_squared()
self.angle = gr.complex_to_arg()
self.sample_and_hold = gr.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = gr.add_const_ff(-1)
self.pk_detect = gr.peak_detector_fb(
0.20, 0.20, 30, 0.001
) #apurv - implementing Veljo's suggestion, when pause b/w packets
self.connect(self, self.input)
# Calculate the frequency offset from the correlation of the preamble
self.connect(self.input, self.delay)
self.connect(self.input, (self.corr, 0))
self.connect(self.delay, self.conjg)
self.connect(self.conjg, (self.corr, 1))
self.connect(self.corr, self.moving_sum_filter)
#self.connect(self.moving_sum_filter, self.c2mag)
self.connect(self.moving_sum_filter, self.angle)
self.connect(self.angle, (self.sample_and_hold, 0)) # apurv--
#self.connect(self.angle, gr.delay(gr.sizeof_float, offset), (self.sample_and_hold, 0)) #apurv++
cross_correlate = 1
if cross_correlate == 1:
# cross-correlate with the known symbol
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.crosscorr_filter = gr.fir_filter_ccc(1, kstime)
# get the magnitude #
self.corrmag = gr.complex_to_mag_squared()
self.f2b = gr.float_to_char()
self.threshold_factor = threshold #0.0012 #0.012 #0.0015
if 0:
self.slice = gr.threshold_ff(self.threshold_factor,
self.threshold_factor, 0,
fft_length)
else:
#thresholds = [self.threshold_factor, 9e-5]
self.slice = gr.threshold_ff(threshold, threshold, 0,
fft_length, threshold_type,
threshold_gap)
self.connect(self.input, self.crosscorr_filter, self.corrmag,
self.slice, self.f2b)
# some debug dump #
self.connect(self.corrmag,
gr.file_sink(gr.sizeof_float, "ofdm_corrmag.dat"))
#self.connect(self.f2b, gr.file_sink(gr.sizeof_char, "ofdm_f2b.dat"))
self.connect(self.f2b, (self.sample_and_hold, 1))
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self, 0))
#self.connect(self.pk_detect, (self,1)) #removed
#self.connect(self.f2b, gr.delay(gr.sizeof_char, 1), (self, 1))
self.connect(self.f2b, (self, 1))
if logging:
self.connect(
self.matched_filter,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-mf_f.dat"))
self.connect(
self.normalize,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-theta_f.dat"))
self.connect(
self.angle,
gr.file_sink(gr.sizeof_float, "ofdm_sync_pn-epsilon_f.dat"))
self.connect(
self.pk_detect,
gr.file_sink(gr.sizeof_char, "ofdm_sync_pn-peaks_b.dat"))
self.connect(
self.sample_and_hold,
gr.file_sink(gr.sizeof_float,
"ofdm_sync_pn-sample_and_hold_f.dat"))
self.connect(
self.input,
gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_pn-input_c.dat"))
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
