def test_012_disconnect_input(self):
hblock = gr.hier_block2("test_block",
gr.io_signature(1,1,gr.sizeof_int),
gr.io_signature(1,1,gr.sizeof_int))
nop1 = blocks.nop(gr.sizeof_int)
hblock.connect(hblock, nop1)
hblock.disconnect(hblock, nop1)
def __init__(self):
gr.hier_block2.__init__(
self, "NBFM Chain",
gr.io_signature(1, 1, gr.sizeof_gr_complex*1),
gr.io_signature(1, 1, gr.sizeof_float*1),
)
##################################################
# Blocks
##################################################
self.rational_resampler_xxx_0 = filter.rational_resampler_ccc(
interpolation=192000,
decimation=2400000,
taps=None,
fractional_bw=None,
)
self.low_pass_filter_1 = filter.fir_filter_ccf(1, firdes.low_pass(
1, 192000, 5e3, 5e3, firdes.WIN_HAMMING, 6.76))
self.blocks_multiply_const_vxx_0 = blocks.multiply_const_vff((5, ))
self.analog_nbfm_rx_0 = analog.nbfm_rx(
audio_rate=48000,
quad_rate=192000,
tau=75e-6,
max_dev=2.5e3,
)
##################################################
# Connections
##################################################
self.connect((self.analog_nbfm_rx_0, 0), (self.blocks_multiply_const_vxx_0, 0))
self.connect((self.blocks_multiply_const_vxx_0, 0), (self, 0))
self.connect((self.low_pass_filter_1, 0), (self.analog_nbfm_rx_0, 0))
self.connect((self, 0), (self.rational_resampler_xxx_0, 0))
self.connect((self.rational_resampler_xxx_0, 0), (self.low_pass_filter_1, 0))
def __init__(self, size, factor, itemsize=gr.sizeof_gr_complex):
"""
size: (int) vector size (FFT size) of next block
factor: (int) output will have this many more samples than input
If size is not divisible by factor, then the output will necessarily have jitter.
"""
size = int(size)
factor = int(factor)
# assert size % factor == 0
offset = size // factor
gr.hier_block2.__init__(
self, type(self).__name__,
gr.io_signature(1, 1, itemsize),
gr.io_signature(1, 1, itemsize),
)
if factor == 1:
# No duplication needed; simplify flowgraph
# GR refused to connect self to self, so insert a dummy block
self.connect(self, blocks.copy(itemsize), self)
else:
interleave = blocks.interleave(itemsize * size)
self.connect(
interleave,
blocks.vector_to_stream(itemsize, size),
self)
for i in xrange(0, factor):
self.connect(
self,
blocks.delay(itemsize, (factor - 1 - i) * offset),
blocks.stream_to_vector(itemsize, size),
(interleave, i))
def test_016_disconnect_output(self):
hblock = gr.hier_block2("test_block",
gr.io_signature(1,1,gr.sizeof_int),
gr.io_signature(1,1,gr.sizeof_int))
nop1 = blocks.nop(gr.sizeof_int)
hblock.connect(nop1, hblock)
hblock.disconnect(nop1, hblock)
def __init__(self, fft_length, occupied_tones, carrier_map_bin):
"""
Hierarchical block for receiving OFDM symbols.
"""
gr.hier_block2.__init__(self, "ncofdm_filt",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Input signature
# fft length, e.g. 256
self._fft_length = fft_length
# the number of used subcarriers, e.g. 240
self._occupied_tones = occupied_tones
# a binary array indicates the used subcarriers
self._carrier_map_bin = carrier_map_bin
# setup filter banks
self.chan_filt_low = filter.fft_filter_ccc(1,[1])
self.chan_filt_high1 = filter.fft_filter_ccc(1,[1])
self.chan_filt_high2 = filter.fft_filter_ccc(1,[1])
self.chan_filt_high3 = filter.fft_filter_ccc(1,[1])
self.chan_filt_high4 = filter.fft_filter_ccc(1,[1])
self.chan_filt_high5 = filter.fft_filter_ccc(1,[1])
# calculate the filter taps
filt_num = self.calc_filter_taps(2, 0)
# signals run into a serial of filters, one lowpass filter and 5 highpass filters
self.connect(self, self.chan_filt_high1,
self.chan_filt_high2, self.chan_filt_high3,
self.chan_filt_high4, self.chan_filt_high5,
self.chan_filt_low, self)
def __init__(self, access_code='', threshold=-1, callback=None, verbose=0): """ packet_demod constructor. @param access_code AKA sync vector @param threshold detect access_code with up to threshold bits wrong (0 -> use default) @param callback a function of args: ok, payload """ #access code if not access_code: #get access code access_code = packet_utils.default_access_code if not packet_utils.is_1_0_string(access_code): raise ValueError, "Invalid access_code %r. Must be string of 1's and 0's" % (access_code,) self._access_code = access_code #threshold if threshold < 0: threshold = DEFAULT_THRESHOLD self._threshold = threshold #blocks msgq = gr.msg_queue(DEFAULT_MSGQ_LIMIT) #holds packets from the PHY correlator = digital.correlate_access_code_bb(self._access_code, self._threshold) framer_sink = logitech_27mhz_transceiver.framer_sink(msgq) #initialize hier2 gr.hier_block2.__init__( self, "packet_decoder", gr.io_signature(1, 1, gr.sizeof_char), # Input signature gr.io_signature(0, 0, 0) # Output signature ) #connect self.connect(self, correlator, framer_sink) #start thread _packet_decoder_thread(msgq, callback,verbose)
def __init__(self, samples_per_symbol, bits_per_symbol, access_code='', pad_for_usrp=True, kbid='', verbose=0): """ packet_mod constructor. @param samples_per_symbol number of samples per symbol @param bits_per_symbol number of bits per symbol @param access_code AKA sync vector @param pad_for_usrp If true, packets are padded such that they end up a multiple of 128 samples @param payload_length number of bytes in a data-stream slice """ #setup parameters self._samples_per_symbol = samples_per_symbol self._bits_per_symbol = bits_per_symbol self._kbid = kbid self._verbose = verbose if not access_code: #get access code access_code = packet_utils.default_access_code if not packet_utils.is_1_0_string(access_code): raise ValueError, "Invalid access_code %r. Must be string of 1's and 0's" % (access_code,) self._access_code = access_code self._pad_for_usrp = pad_for_usrp #create blocks msg_source = gr.message_source(gr.sizeof_char, DEFAULT_MSGQ_LIMIT) self._msgq_out = msg_source.msgq() #initialize hier2 gr.hier_block2.__init__( self, "packet_encoder", gr.io_signature(0, 0, 0), # Input signature gr.io_signature(1, 1, gr.sizeof_char) # Output signature ) #connect self.connect(msg_source, self)
def __init__(self, sample_rate, symbol_rate): gr.hier_block2.__init__(self, "dvb_s_demodulator_cc", gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature omega = sample_rate / symbol_rate gain_omega = omega * omega / 4.0 freq_beta = freq_alpha * freq_alpha / 4.0 mu = 0.0 gain_mu = 0.05 omega_relative_limit = 0.005 # Automatic gain control self.agc = gr.agc2_cc( 0.06, # Attack rate 0.001, # Decay rate 1, # Reference 1, # Initial gain 100) # Max gain # Frequency correction with band-edge filters FLL freq_beta = freq_alpha * freq_alpha / 4 self.freq_recov = digital.fll_band_edge_cc(omega, dvb_swig.RRC_ROLLOFF_FACTOR, 11 * int(omega), freq_bw) self.freq_recov.set_alpha(freq_alpha) self.freq_recov.set_beta(freq_beta) self.receiver = digital.mpsk_receiver_cc(M, 0, freq_bw, fmin, fmax, mu, gain_mu, omega, gain_omega, omega_relative_limit) self.receiver.set_alpha(freq_alpha) self.receiver.set_beta(freq_beta) self.rotate = gr.multiply_const_cc(0.707 + 0.707j) self.connect(self, self.agc, self.freq_recov, self.receiver, self.rotate, self)
def __init__(self, bitrate,
constellation, samples_per_symbol,
differential, excess_bw, gray_coded,
freq_bw, timing_bw, phase_bw,
verbose, log):
gr.hier_block2.__init__(self, "bert_receive",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
self._bitrate = bitrate
self._demod = digital.generic_demod(constellation, differential,
samples_per_symbol,
gray_coded, excess_bw,
freq_bw, timing_bw, phase_bw,
verbose, log)
self._symbol_rate = self._bitrate / self._demod.bits_per_symbol()
self._sample_rate = self._symbol_rate * samples_per_symbol
# Add an SNR probe on the demodulated constellation
self._snr_probe = digital.probe_mpsk_snr_est_c(digital.SNR_EST_M2M4, 1000,
alpha=10.0/self._symbol_rate)
self.connect(self._demod.time_recov, self._snr_probe)
# Descramble BERT sequence. A channel error will create 3 incorrect bits
self._descrambler = digital.descrambler_bb(0x8A, 0x7F, 7) # CCSDS 7-bit descrambler
# Measure BER by the density of 0s in the stream
self._ber = digital.probe_density_b(1.0/self._symbol_rate)
self.connect(self, self._demod, self._descrambler, self._ber)
def __init__(self, input_is_real=False, baseband_freq=0, y_per_div=10, ref_level=50,
sample_rate=1, fac_size=512,
fac_rate=default_fac_rate,
average=False, avg_alpha=None, title='', peak_hold=False):
self._item_size = gr.sizeof_gr_complex
if input_is_real:
self._item_size = gr.sizeof_float
gr.hier_block2.__init__(
self,
"Fast AutoCorrelation",
gr.io_signature(1, 1, self._item_size),
gr.io_signature(0, 0, 0),
)
# initialize common attributes
self.baseband_freq = baseband_freq
self.y_divs = 8
self.y_per_div=y_per_div
self.ref_level = ref_level
self.sample_rate = sample_rate
self.fac_size = fac_size
self.fac_rate = fac_rate
self.average = average
if (avg_alpha is None) or (avg_alpha <= 0):
self.avg_alpha = 0.20 / fac_rate # averaging needed to be slowed down for very slow rates
else:
self.avg_alpha = avg_alpha
self.title = title
self.peak_hold = peak_hold
self.input_is_real = input_is_real
self.msgq = gr.msg_queue(2) # queue that holds a maximum of 2 messages
def __init__(self,
device_name,
sample_rate,
channel_mapping,
audio_module):
self.__device_name = device_name
self.__sample_rate = sample_rate
self.__signal_type = SignalType(
# TODO: type should be able to be LSB
kind='IQ' if len(channel_mapping) == 2 else 'USB',
sample_rate=self.__sample_rate)
gr.hier_block2.__init__(
self, type(self).__name__,
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(0, 0, 0),
)
sink = audio_module.sink(
self.__sample_rate,
device_name=self.__device_name,
ok_to_block=True)
# TODO: ignoring channel_mapping parameter, shouldn't be
split = blocks.complex_to_float(1)
self.connect(self, split, (sink, 0))
self.connect((split, 1), (sink, 1))
def __init__(self, interp, taps=None, atten=100):
gr.hier_block2.__init__(self, "pfb_interpolator_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self._interp = interp
self._taps = taps
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.99
made = False
while not made:
try:
self._taps = optfir.low_pass(self._interp, self._interp, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_interpolator_ccf(self._interp, self._taps)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, mode, input_rate=0, context=None):
assert input_rate > 0
self.__input_rate = input_rate
gr.hier_block2.__init__(
self, 'RTTY demodulator',
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(1, 1, gr.sizeof_float * 1))
channel_filter = self.__make_channel_filter()
self.__text = u''
self.__char_queue = gr.msg_queue(limit=100)
self.__char_sink = blocks.message_sink(gr.sizeof_char, self.__char_queue, True)
self.connect(
self,
channel_filter,
self.__make_demodulator(),
self.__char_sink)
self.connect(
channel_filter,
self.__make_audio_filter(),
blocks.rotator_cc(rotator_inc(self.__demod_rate, 2000 + self.__spacing / 2)),
blocks.complex_to_real(vlen=1),
analog.agc2_ff(
reference=dB(-10),
attack_rate=8e-1,
decay_rate=8e-1),
self)
def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(self, "pfb_arb_resampler_ccc",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._rate = rate
self._size = flt_size
if (taps is not None) and (len(taps) > 0):
self._taps = taps
else:
# Create a filter that covers the full bandwidth of the input signal
bw = 0.4
tb = 0.2
ripple = 0.1
#self._taps = filter.firdes.low_pass_2(self._size, self._size, bw, tb, atten)
made = False
while not made:
try:
self._taps = optfir.low_pass(self._size, self._size, bw, bw+tb, ripple, atten)
made = True
except RuntimeError:
ripple += 0.01
made = False
print("Warning: set ripple to %.4f dB. If this is a problem, adjust the attenuation or create your own filter taps." % (ripple))
# Build in an exit strategy; if we've come this far, it ain't working.
if(ripple >= 1.0):
raise RuntimeError("optfir could not generate an appropriate filter.")
self.pfb = filter.pfb_arb_resampler_ccc(self._rate, self._taps, self._size)
#print "PFB has %d taps\n" % (len(self._taps),)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, n_chans, n_filterbanks=1, taps=None, outchans=None,
atten=100, bw=1.0, tb=0.2, ripple=0.1):
if n_filterbanks > n_chans:
n_filterbanks = n_chans
if outchans is None:
outchans = range(n_chans)
gr.hier_block2.__init__(
self, "pfb_channelizer_hier_ccf",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(len(outchans), len(outchans), gr.sizeof_gr_complex))
if taps is None:
taps = optfir.low_pass(1, n_chans, bw, bw+tb, ripple, atten)
taps = list(taps)
extra_taps = int(math.ceil(1.0*len(taps)/n_chans)*n_chans - len(taps))
taps = taps + [0] * extra_taps
# Make taps for each channel
chantaps = [list(reversed(taps[i: len(taps): n_chans])) for i in range(0, n_chans)]
# Convert the input stream into a stream of vectors.
self.s2v = blocks.stream_to_vector(gr.sizeof_gr_complex, n_chans)
# Create a mapping to separate out each filterbank (a group of channels to be processed together)
# And a list of sets of taps for each filterbank.
low_cpp = int(n_chans/n_filterbanks)
extra = n_chans - low_cpp*n_filterbanks
cpps = [low_cpp+1]*extra + [low_cpp]*(n_filterbanks-extra)
splitter_mapping = []
filterbanktaps = []
total = 0
for cpp in cpps:
splitter_mapping.append([(0, i) for i in range(total, total+cpp)])
filterbanktaps.append(chantaps[total: total+cpp])
total += cpp
assert(total == n_chans)
# Split the stream of vectors in n_filterbanks streams of vectors.
self.splitter = blocks.vector_map(gr.sizeof_gr_complex, [n_chans], splitter_mapping)
# Create the filterbanks
self.fbs = [filter.filterbank_vcvcf(taps) for taps in filterbanktaps]
# Combine the streams of vectors back into a single stream of vectors.
combiner_mapping = [[]]
for i, cpp in enumerate(cpps):
for j in range(cpp):
combiner_mapping[0].append((i, j))
self.combiner = blocks.vector_map(gr.sizeof_gr_complex, cpps, combiner_mapping)
# Add the final FFT to the channelizer.
self.fft = fft.fft_vcc(n_chans, forward=True, window=[1.0]*n_chans)
# Select the desired channels
if outchans != range(n_chans):
selector_mapping = [[(0, i) for i in outchans]]
self.selector = blocks.vector_map(gr.sizeof_gr_complex, [n_chans], selector_mapping)
# Convert stream of vectors to a normal stream.
self.v2ss = blocks.vector_to_streams(gr.sizeof_gr_complex, len(outchans))
self.connect(self, self.s2v, self.splitter)
for i in range(0, n_filterbanks):
self.connect((self.splitter, i), self.fbs[i], (self.combiner, i))
self.connect(self.combiner, self.fft)
if outchans != range(n_chans):
self.connect(self.fft, self.selector, self.v2ss)
else:
self.connect(self.fft, self.v2ss)
for i in range(0, len(outchans)):
self.connect((self.v2ss, i), (self, i))
def __init__(self, sps, channel_decim, channel_taps, options, usrp_rate, channel_rate, lo_freq):
gr.hier_block2.__init__(self, "rx_channel_cqpsk",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
chan = gr.freq_xlating_fir_filter_ccf(int(channel_decim), channel_taps, lo_freq, usrp_rate)
agc = gr.feedforward_agc_cc(16, 1.0)
gain_omega = 0.125 * options.gain_mu * options.gain_mu
alpha = options.costas_alpha
beta = 0.125 * alpha * alpha
fmin = -0.025
fmax = 0.025
clock = repeater.gardner_costas_cc(sps, options.gain_mu, gain_omega, alpha, beta, fmax, fmin)
# Perform Differential decoding on the constellation
diffdec = gr.diff_phasor_cc()
# take angle of the difference (in radians)
to_float = gr.complex_to_arg()
# convert from radians such that signal is in -3/-1/+1/+3
rescale = gr.multiply_const_ff( (1 / (pi / 4)) )
self.connect (self, chan, agc, clock, diffdec, to_float, rescale, self)
def __init__(self, sps, channel_decim, channel_taps, options, usrp_rate, channel_rate, lo_freq, max_dev, ctcss):
gr.hier_block2.__init__(self, "rx_channel_nfm",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
# gr.io_signature(0, 0, 0))
gr.io_signature(1, 1, gr.sizeof_float))
output_sample_rate = 8000
chan = gr.freq_xlating_fir_filter_ccf(int(channel_decim), channel_taps, lo_freq, usrp_rate)
nphases = 32
frac_bw = 0.45
rs_taps = gr.firdes.low_pass(nphases, nphases, frac_bw, 0.5-frac_bw)
resampler = blks2.pfb_arb_resampler_ccf(
float(output_sample_rate)/channel_rate,
(rs_taps),
nphases
)
# FM Demodulator input: complex; output: float
k = output_sample_rate/(2*math.pi*max_dev)
fm_demod = gr.quadrature_demod_cf(k)
self.connect (self, chan, resampler, fm_demod)
if ctcss > 0:
level = 5.0
len = 0
ramp = 0
gate = True
ctcss = repeater.ctcss_squelch_ff(output_sample_rate, ctcss, level, len, ramp, gate)
self.connect (fm_demod, ctcss, self)
else:
self.connect (fm_demod, self)
def __init__(self, modulator, audio_rate, rf_rate, freq):
modulator = IModulator(modulator)
gr.hier_block2.__init__(
self, 'SimulatedChannel',
gr.io_signature(1, 1, gr.sizeof_float * 1),
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
)
self.__freq = freq
self.__rf_rate = rf_rate
self.__modulator = modulator
modulator_input_type = modulator.get_input_type()
if modulator_input_type.get_kind() == 'MONO':
audio_resampler = make_resampler(audio_rate, modulator_input_type.get_sample_rate())
self.connect(self, audio_resampler, modulator)
elif modulator_input_type.get_kind() == 'NONE':
self.connect(self, blocks.null_sink(gr.sizeof_float))
else:
raise Exception('don\'t know how to supply input of type %s' % modulator_input_type)
rf_resampler = rational_resampler.rational_resampler_ccf(
interpolation=int(rf_rate),
decimation=int(modulator.get_output_type().get_sample_rate()))
self.__rotator = blocks.rotator_cc(rotator_inc(rate=rf_rate, shift=freq))
self.__mult = blocks.multiply_const_cc(dB(-10))
self.connect(modulator, rf_resampler, self.__rotator, self.__mult, self)
def __init__(self, sps, channel_decim, channel_taps, options, usrp_rate, channel_rate, lo_freq):
gr.hier_block2.__init__(self, "rx_channel_fm",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
chan = gr.freq_xlating_fir_filter_ccf(int(channel_decim), channel_taps, lo_freq, usrp_rate)
symbol_decim = 1
symbol_rate = 4800
self.symbol_deviation = 600.0
fm_demod_gain = channel_rate / (2.0 * pi * self.symbol_deviation)
fm_demod = gr.quadrature_demod_cf(fm_demod_gain)
symbol_coeffs = gr.firdes_root_raised_cosine(1.0,
channel_rate,
symbol_rate,
1.0,
51)
symbol_filter = gr.fir_filter_fff(symbol_decim, symbol_coeffs)
# C4FM demodulator
autotuneq = gr.msg_queue(2)
demod_fsk4 = fsk4.demod_ff(autotuneq, channel_rate, symbol_rate)
self.connect (self, chan, fm_demod, symbol_filter, demod_fsk4, self)
def __init__(self, options):
gr.hier_block2.__init__(self, "ais_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
self._samples_per_symbol = options[ "samples_per_symbol" ]
self._bits_per_sec = options[ "bits_per_sec" ]
self._samplerate = self._samples_per_symbol * self._bits_per_sec
self._clockrec_gain = options[ "clockrec_gain" ]
self._omega_relative_limit = options[ "omega_relative_limit" ]
self.fftlen = options[ "fftlen" ]
self.freq_sync = gmsk_sync.square_and_fft_sync_cc(self._samplerate, self._bits_per_sec, self.fftlen)
self.agc = analog.feedforward_agc_cc(512, 2)
self.preamble = [1,1,0,0]*7
self.mod = digital.gmsk_mod(self._samples_per_symbol, 0.4)
self.mod_vector = ais.modulate_vector_bc(self.mod.to_basic_block(), self.preamble, [1])
self.preamble_detect = ais.corr_est_cc(self.mod_vector,
self._samples_per_symbol,
1, #mark delay
0.9) #threshold
self.clockrec = ais.msk_timing_recovery_cc(self._samples_per_symbol,
self._clockrec_gain, #gain
self._omega_relative_limit, #error lim
1) #output sps
sensitivity = (math.pi / 2)
self.demod = analog.quadrature_demod_cf(sensitivity) #param is gain
self.slicer = digital.binary_slicer_fb()
self.diff = digital.diff_decoder_bb(2)
self.invert = ais.invert() #NRZI signal diff decoded and inverted should give original signal
# self.connect(self, self.gmsk_sync)
self.connect(self, self.freq_sync, self.agc, (self.preamble_detect, 0), self.clockrec, self.demod, self.slicer, self.diff, self.invert, self)
def __init__(self, mode, input_rate, output_rate, mod_class=None):
gr.hier_block2.__init__(
self, type(self).__name__,
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
if mod_class is None:
mode_def = lookup_mode(mode)
if mode_def is None:
raise Exception('{}: No modulator registered for mode {!r}, only {!r}'.format(
type(self).__name__, mode, [md.mode for md in get_modes() if md.mod_class]))
mod_class = mode_def.mod_class
context = _ModulatorAdapterContext(adapter=self)
modulator = self.__modulator = IModulator(mod_class(
mode=mode,
context=context))
self.__connect_with_resampling(
self, input_rate,
modulator, modulator.get_input_type().get_sample_rate(),
False)
self.__connect_with_resampling(
modulator, modulator.get_output_type().get_sample_rate(),
self, output_rate,
True)
def __init__(self, device_name, sample_rate, quadrature_as_stereo): self.__device_name = device_name self.__sample_rate = sample_rate self.__quadrature_as_stereo = quadrature_as_stereo if self.__quadrature_as_stereo: self.__signal_type = SignalType( kind='IQ', sample_rate=self.__sample_rate) else: self.__signal_type = SignalType( kind='USB', # TODO obtain correct type from config (or say hamlib) sample_rate=self.__sample_rate) gr.hier_block2.__init__( self, type(self).__name__, gr.io_signature(0, 0, 0), gr.io_signature(1, 1, gr.sizeof_gr_complex * 1), ) self.__source = audio.source( self.__sample_rate, device_name=self.__device_name, ok_to_block=True) combine = blocks.float_to_complex(1) self.connect(self.__source, combine, self) if self.__quadrature_as_stereo: # if we don't do this, the imaginary component is 0 and the spectrum is symmetric self.connect((self.__source, 1), (combine, 1))
def __init__(self,
sps, # Samples per symbol
excess_bw, # RRC filter excess bandwidth (typically 0.35-0.5)
amplitude, # DAC output level, 0-32767, typically 2000-8000
vector_source, # Indicate if it's the infinite sequence of 1, or by use the code to change the amplitude
):
gr.hier_block2.__init__(self, "bpsk_modulator",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
# Create BERT data bit stream
self.vector_source = vector_source
self._scrambler = gr.scrambler_bb(0x8A, 0x7F, 31) # CCSDS 7-bit scrambler
# Map to constellation
self._constellation = [-1+0j, 1+0j]
self._mapper = gr.chunks_to_symbols_bc(self._constellation)
# Create RRC with specified excess bandwidth
taps = gr.firdes.root_raised_cosine(sps, # Gain
sps, # Sampling rate
1.0, # Symbol rate
excess_bw, # Roll-off factor
11*sps) # Number of taps
self._rrc = gr.interp_fir_filter_ccf(sps, # Interpolation rate
taps) # FIR taps
self.amp = gr.multiply_const_cc(amplitude)
# Wire block inputs and outputs
self.connect(self.vector_source, self._scrambler, self._mapper, self._rrc, self.amp, self)
def test_005_connect_invalid_src_port_exceeds(self):
hblock = gr.hier_block2("test_block",
gr.io_signature(1,1,gr.sizeof_int),
gr.io_signature(1,1,gr.sizeof_int))
nop1 = blocks.nop(gr.sizeof_int)
self.assertRaises(RuntimeError,
lambda: hblock.connect((hblock, 1), nop1))
def __init__(self, queue, freq=0.0, verbose=False, log=False):
gr.hier_block2.__init__(self, "flex_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0,0,0))
k = 25000/(2*pi*1600) # 4800 Hz max deviation
quad = gr.quadrature_demod_cf(k)
self.connect(self, quad)
rsamp = blks2.rational_resampler_fff(16, 25)
self.slicer = pager_swig.slicer_fb(5e-6) # DC removal averaging filter constant
self.sync = pager_swig.flex_sync()
self.connect(quad, rsamp, self.slicer, self.sync)
for i in range(4):
self.connect((self.sync, i), pager_swig.flex_deinterleave(), pager_swig.flex_parse(queue, freq))
if log:
suffix = '_'+ "%3.3f" % (freq/1e6,) + '.dat'
quad_sink = gr.file_sink(gr.sizeof_float, 'quad'+suffix)
rsamp_sink = gr.file_sink(gr.sizeof_float, 'rsamp'+suffix)
slicer_sink = gr.file_sink(gr.sizeof_char, 'slicer'+suffix)
self.connect(rsamp, rsamp_sink)
self.connect(quad, quad_sink)
self.connect(self.slicer, slicer_sink)
def test_024_disconnect_single(self):
hblock = gr.top_block("test_block")
blk = gr.hier_block2("block",
gr.io_signature(0, 0, 0),
gr.io_signature(0, 0, 0))
hblock.connect(blk)
hblock.disconnect(blk)
def test_025_disconnect_single_not_connected(self):
hblock = gr.top_block("test_block")
blk = gr.hier_block2("block",
gr.io_signature(0, 0, 0),
gr.io_signature(0, 0, 0))
self.assertRaises(RuntimeError,
lambda: hblock.disconnect(blk))
def __init__(self, dest, key):
gr.hier_block2.__init__(
self, self.__class__.__name__,
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1))
self.__dest = dest
self.__key = key
def test_022_connect_single_with_ports(self):
hblock = gr.top_block("test_block")
blk = gr.hier_block2("block",
gr.io_signature(1, 1, 1),
gr.io_signature(1, 1, 1))
self.assertRaises(RuntimeError,
lambda: hblock.connect(blk))
def __init__(self, device_name, sample_rate, quadrature_as_stereo): self.__device_name = device_name self.__sample_rate = sample_rate self.__quadrature_as_stereo = quadrature_as_stereo self.__signal_type = SignalType( # TODO: type should be able to be LSB kind='IQ' if quadrature_as_stereo else 'USB', sample_rate=self.__sample_rate) gr.hier_block2.__init__( self, type(self).__name__, gr.io_signature(1, 1, gr.sizeof_gr_complex * 1), gr.io_signature(0, 0, 0), ) sink = audio.sink( self.__sample_rate, device_name=self.__device_name, ok_to_block=True) split = blocks.complex_to_float(1) self.connect(self, split, (sink, 0)) self.connect((split, 1), (sink, 1))
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
excess_bw=_def_excess_bw,
gray_code=_def_gray_code,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for RRC-filtered QPSK modulation.
The input is a byte stream (unsigned char) and the
output is the complex modulated signal at baseband.
@param samples_per_symbol: samples per symbol >= 2
@type samples_per_symbol: integer
@param excess_bw: Root-raised cosine filter excess bandwidth
@type excess_bw: float
@param gray_code: Tell modulator to Gray code the bits
@type gray_code: bool
@param verbose: Print information about modulator?
@type verbose: bool
@param debug: Print modualtion data to files?
@type debug: bool
"""
gr.hier_block2.__init__(
self,
"qam64_mod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._samples_per_symbol = samples_per_symbol
self._excess_bw = excess_bw
self._gray_code = gray_code
if not isinstance(samples_per_symbol, int) or samples_per_symbol < 2:
raise TypeError, ("sbp must be an integer >= 2, is %d" %
samples_per_symbol)
ntaps = 11 * samples_per_symbol
arity = pow(2, self.bits_per_symbol())
# turn bytes into k-bit vectors
self.bytes2chunks = \
gr.packed_to_unpacked_bb(self.bits_per_symbol(), gr.GR_MSB_FIRST)
if self._gray_code:
self.symbol_mapper = gr.map_bb(qam.binary_to_gray[arity])
else:
self.symbol_mapper = gr.map_bb(qam.binary_to_ungray[arity])
self.diffenc = gr.diff_encoder_bb(arity)
rot = 1.0
print "constellation with %d arity" % arity
rotated_const = map(lambda pt: pt * rot, qam.constellation[arity])
self.chunks2symbols = gr.chunks_to_symbols_bc(rotated_const)
# pulse shaping filter
self.rrc_taps = gr.firdes.root_raised_cosine(
self.
_samples_per_symbol, # gain (sps since we're interpolating by sps)
self._samples_per_symbol, # sampling rate
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = gr.interp_fir_filter_ccf(self._samples_per_symbol,
self.rrc_taps)
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Connect
self.connect(self, self.bytes2chunks, self.symbol_mapper, self.diffenc,
self.chunks2symbols, self.rrc_filter, self)
def __init__(self, options, msgq_limit=2, pad_for_usrp=True):
"""
Hierarchical block for sending packets
Packets to be sent are enqueued by calling send_pkt.
The output is the complex modulated signal at baseband.
Args:
options: pass modulation options from higher layers (fft length, occupied tones, etc.)
msgq_limit: maximum number of messages in message queue (int)
pad_for_usrp: If true, packets are padded such that they end up a multiple of 128 samples
"""
gr.hier_block2.__init__(
self,
"ofdm_mod",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._pad_for_usrp = pad_for_usrp
self._modulation = options.modulation
self._fft_length = options.fft_length
self._occupied_tones = options.occupied_tones
self._cp_length = options.cp_length
win = [] #[1 for i in range(self._fft_length)]
# Use freq domain to get doubled-up known symbol for correlation in time domain
zeros_on_left = int(
math.ceil((self._fft_length - self._occupied_tones) / 2.0))
ksfreq = known_symbols_4512_3[0:self._occupied_tones]
for i in range(len(ksfreq)):
if ((zeros_on_left + i) & 1):
ksfreq[i] = 0
# hard-coded known symbols
preambles = (ksfreq, )
padded_preambles = list()
for pre in preambles:
padded = self._fft_length * [
0,
]
padded[zeros_on_left:zeros_on_left + self._occupied_tones] = pre
padded_preambles.append(padded)
symbol_length = options.fft_length + options.cp_length
mods = {
"bpsk": 2,
"qpsk": 4,
"8psk": 8,
"qam8": 8,
"qam16": 16,
"qam64": 64,
"qam256": 256
}
arity = mods[self._modulation]
rot = 1
if self._modulation == "qpsk":
rot = (0.707 + 0.707j)
# FIXME: pass the constellation objects instead of just the points
if (self._modulation.find("psk") >= 0):
constel = psk.psk_constellation(arity)
rotated_const = map(lambda pt: pt * rot, constel.points())
elif (self._modulation.find("qam") >= 0):
constel = qam.qam_constellation(arity)
rotated_const = map(lambda pt: pt * rot, constel.points())
#print rotated_const
self._pkt_input = digital.ofdm_mapper_bcv(rotated_const, msgq_limit,
options.occupied_tones,
options.fft_length)
self.preambles = digital.ofdm_insert_preamble(self._fft_length,
padded_preambles)
self.ifft = fft.fft_vcc(self._fft_length, False, win, True)
self.cp_adder = digital.ofdm_cyclic_prefixer(self._fft_length,
symbol_length)
self.scale = blocks.multiply_const_cc(1.0 /
math.sqrt(self._fft_length))
self.connect((self._pkt_input, 0), (self.preambles, 0))
self.connect((self._pkt_input, 1), (self.preambles, 1))
self.connect(self.preambles, self.ifft, self.cp_adder, self.scale,
self)
class receiver(gr.hier_block2): def __init__(self): gr.hier_block2.__init__(self, "ofdm_tx", gr.io_signature(1, 1, gr.sizeof_gr_complex), gr.io_signature(1, 1, gr.sizeof_char))
def __init__(self, mode='433', input_rate=0, context=None):
assert input_rate > 0
assert context is not None
gr.hier_block2.__init__(self,
type(self).__name__,
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0, 0, 0))
# The input bandwidth chosen is not primarily determined by the bandwidth of the input signals, but by the frequency error of the transmitters. Therefore it is not too critical, and we can choose the exact rate to make the filtering easy.
if input_rate <= upper_preferred_demod_rate:
# Skip having a filter at all.
self.__band_filter = None
demod_rate = input_rate
else:
# TODO: This gunk is very similar to the stuff that MultistageChannelFilter does. See if we can share some code.
lower_rate = input_rate
lower_rate_prev = None
while lower_rate > upper_preferred_demod_rate and lower_rate != lower_rate_prev:
lower_rate_prev = lower_rate
if lower_rate % 5 == 0 and lower_rate > upper_preferred_demod_rate * 3:
lower_rate /= 5
elif lower_rate % 2 == 0:
lower_rate /= 2
else:
# non-integer ratio
lower_rate = upper_preferred_demod_rate
break
demod_rate = lower_rate
self.__band_filter = MultistageChannelFilter(
input_rate=input_rate,
output_rate=demod_rate,
cutoff_freq=demod_rate * 0.4,
transition_width=demod_rate * 0.2)
# Subprocess
# using /usr/bin/env because twisted spawnProcess doesn't support path search
# pylint: disable=no-member
self.__process = the_reactor.spawnProcess(
RTL433ProcessProtocol(context.output_message, self.__log),
'/usr/bin/env',
env=None, # inherit environment
args=[
b'env',
b'rtl_433',
b'-F',
b'json',
b'-r',
b'-', # read from stdin
b'-m',
b'3', # complex float input
b'-s',
str(demod_rate),
b'-q' # quiet mode, suppress "Registering protocol..." stderr flood
],
childFDs={
0: 'w',
1: 'r',
2: 2
})
sink = make_sink_to_process_stdin(self.__process,
itemsize=gr.sizeof_gr_complex)
agc = analog.agc2_cc(reference=dB(-4))
agc.set_attack_rate(200 / demod_rate)
agc.set_decay_rate(200 / demod_rate)
if self.__band_filter:
self.connect(self, self.__band_filter, agc)
else:
self.connect(self, agc)
self.connect(agc, sink)
def __init__(self,
input_rate=None,
demod_type='cqpsk',
filter_type=None,
excess_bw=_def_excess_bw,
relative_freq=0,
offset=0,
if_rate=_def_if_rate,
gain_mu=_def_gain_mu,
costas_alpha=_def_costas_alpha,
symbol_rate=_def_symbol_rate):
"""
Hierarchical block for P25 demodulation.
The complex input is tuned, decimated and demodulated
@param input_rate: sample rate of complex input channel
@type input_rate: int
"""
gr.hier_block2.__init__(
self,
"p25_demod_cb",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
# gr.io_signature(0, 0, 0)) # Output signature
p25_demod_base.__init__(self,
if_rate=if_rate,
symbol_rate=symbol_rate,
filter_type=filter_type)
self.input_rate = input_rate
self.if_rate = if_rate
self.symbol_rate = symbol_rate
self.connect_state = None
self.offset = 0
self.sps = 0.0
self.lo_freq = 0
self.float_sink = None
self.complex_sink = None
self.if1 = 0
self.if2 = 0
self.t_cache = {}
if filter_type == 'rrc':
self.set_baseband_gain(0.61)
self.mixer = blocks.multiply_cc()
decimator_values = get_decim(input_rate)
if decimator_values:
self.decim, self.decim2 = decimator_values
self.if1 = input_rate / self.decim
self.if2 = self.if1 / self.decim2
sys.stderr.write(
'Using two-stage decimator for speed=%d, decim=%d/%d if1=%d if2=%d\n'
% (input_rate, self.decim, self.decim2, self.if1, self.if2))
bpf_coeffs = filter.firdes.complex_band_pass(
1.0, input_rate, -self.if1 / 2, self.if1 / 2, self.if1 / 2,
filter.firdes.WIN_HAMMING)
self.t_cache[0] = bpf_coeffs
fa = 6250
fb = self.if2 / 2
if filter_type == 'nxdn' and self.symbol_rate == 2400: # nxdn48 6.25 KHz
fa = 3125
lpf_coeffs = filter.firdes.low_pass(1.0, self.if1, (fb + fa) / 2,
fb - fa,
filter.firdes.WIN_HAMMING)
self.bpf = filter.fir_filter_ccc(self.decim, bpf_coeffs)
self.lpf = filter.fir_filter_ccf(self.decim2, lpf_coeffs)
resampled_rate = self.if2
self.relative_limit = (input_rate // 2) - (self.if1 // 2)
self.bfo = analog.sig_source_c(self.if1, analog.GR_SIN_WAVE, 0,
1.0, 0)
self.connect(self, self.bpf, (self.mixer, 0))
self.connect(self.bfo, (self.mixer, 1))
else:
sys.stderr.write(
'Unable to use two-stage decimator for speed=%d\n' %
(input_rate))
# local osc
self.lo = analog.sig_source_c(input_rate, analog.GR_SIN_WAVE, 0,
1.0, 0)
f1 = 7250
f2 = 1450
if filter_type == 'nxdn' and self.symbol_rate == 2400: # nxdn48 6.25 KHz
f1 = 3125
f2 = 625
lpf_coeffs = filter.firdes.low_pass(1.0, input_rate, f1, f2,
filter.firdes.WIN_HANN)
decimation = int(input_rate / if_rate)
self.lpf = filter.fir_filter_ccf(decimation, lpf_coeffs)
resampled_rate = float(input_rate) / float(
decimation) # rate at output of self.lpf
self.relative_limit = (input_rate // 2) - f1
self.connect(self, (self.mixer, 0))
self.connect(self.lo, (self.mixer, 1))
self.connect(self.mixer, self.lpf)
if self.if_rate != resampled_rate:
self.if_out = filter.pfb.arb_resampler_ccf(
float(self.if_rate) / resampled_rate)
self.connect(self.lpf, self.if_out)
else:
self.if_out = self.lpf
fa = 6250
fb = fa + 625
cutoff_coeffs = filter.firdes.low_pass(1.0, self.if_rate,
(fb + fa) / 2, fb - fa,
filter.firdes.WIN_HANN)
self.cutoff = filter.fir_filter_ccf(1, cutoff_coeffs)
omega = float(self.if_rate) / float(self.symbol_rate)
gain_omega = 0.1 * gain_mu * gain_mu
alpha = costas_alpha
beta = 0.125 * alpha * alpha
fmax = 2400 # Hz
fmax = 2 * pi * fmax / float(self.if_rate)
self.clock = op25_repeater.gardner_costas_cc(omega, gain_mu,
gain_omega, alpha, beta,
fmax, -fmax)
self.agc = analog.feedforward_agc_cc(16, 1.0)
# Perform Differential decoding on the constellation
self.diffdec = digital.diff_phasor_cc()
# take angle of the difference (in radians)
self.to_float = blocks.complex_to_arg()
# convert from radians such that signal is in -3/-1/+1/+3
self.rescale = blocks.multiply_const_ff((1 / (pi / 4)))
# fm demodulator (needed in fsk4 case)
fm_demod_gain = if_rate / (2.0 * pi * _def_symbol_deviation)
self.fm_demod = analog.quadrature_demod_cf(fm_demod_gain)
self.connect_chain(demod_type)
self.connect(self.slicer, self)
self.set_relative_frequency(relative_freq)
def __init__(
self,
verbose_mode=True,
radio_device_name="/dev/ndr47x",
radio_baud_rate=921600,
gig_iface_to_use="eth0",
num_tuners=1,
tuner1_param_list=[False, 900e6, 0],
tuner2_param_list=[False, 900e6, 0],
num_wbddcs=1,
wbddc1_param_list=[40001, 0, 0, False, 0e6],
wbddc2_param_list=[40002, 0, 0, False, 0e6],
tagged=False,
):
gr.hier_block2.__init__(
self,
"[CyberRadio] NDR472 Source",
gr.io_signature(0, 0, 0),
gr.io_signaturev(num_wbddcs + 1, num_wbddcs + 1,
[gr.sizeof_char * 1] +
num_wbddcs * [gr.sizeof_gr_complex * 1]),
)
self.verbose_mode = verbose_mode
self.radio_device_name = radio_device_name
self.radio_baud_rate = radio_baud_rate
self.gig_iface_to_use = gig_iface_to_use
self.udp_host_name = CyberRadioDriver.getInterfaceAddresses(
self.gig_iface_to_use)[1]
self.num_tuners = num_tuners
self.tuner1_param_list = tuner1_param_list
self.tuner2_param_list = tuner2_param_list
self.num_wbddcs = num_wbddcs
self.wbddc1_param_list = wbddc1_param_list
self.wbddc2_param_list = wbddc2_param_list
self.tagged = tagged
self.CyberRadio_file_like_object_source_0 = CyberRadio.file_like_object_source(
)
self.connect((self.CyberRadio_file_like_object_source_0, 0), (self, 0))
self.CyberRadio_NDR_driver_interface_0 = CyberRadio.NDR_driver_interface(
radio_type="ndr472",
verbose=verbose_mode,
log_file=self.CyberRadio_file_like_object_source_0,
connect_mode="tty",
dev_name=radio_device_name,
baud_rate=radio_baud_rate,
)
self.vita_tail_size = self.CyberRadio_NDR_driver_interface_0.getVitaTailSize(
)
self.vita_payload_size = self.CyberRadio_NDR_driver_interface_0.getVitaPayloadSize(
)
self.vita_header_size = self.CyberRadio_NDR_driver_interface_0.getVitaHeaderSize(
)
self.iq_swapped = self.CyberRadio_NDR_driver_interface_0.isIqSwapped()
self.byte_swapped = self.CyberRadio_NDR_driver_interface_0.isByteswapped(
)
self._set_udp_dest_info()
if self.num_tuners >= 1:
self._set_tuner_param_list(1, tuner1_param_list)
if self.num_tuners >= 2:
self._set_tuner_param_list(2, tuner2_param_list)
self.wbddc_sources = {}
if self.num_wbddcs >= 1:
self.CyberRadio_vita_iq_source_wbddc_1 = self._get_configured_wbddc(
1, wbddc1_param_list)
self.connect((self.CyberRadio_vita_iq_source_wbddc_1, 0),
(self, 1))
self.wbddc_sources[1] = self.CyberRadio_vita_iq_source_wbddc_1
if self.num_wbddcs >= 2:
self.CyberRadio_vita_iq_source_wbddc_2 = self._get_configured_wbddc(
2, wbddc2_param_list)
self.connect((self.CyberRadio_vita_iq_source_wbddc_2, 0),
(self, 2))
self.wbddc_sources[2] = self.CyberRadio_vita_iq_source_wbddc_2
def __init__(self, options, log=False):
## Read configuration
config = station_configuration()
fft_length = config.fft_length
#cp_length = config.cp_length
block_header = config.training_data
data_subc = config.data_subcarriers
virtual_subc = config.virtual_subcarriers
total_subc = config.subcarriers
block_length = config.block_length
frame_length = config.frame_length
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, callback=None):
"""
Hierarchical block for demodulating and deframing packets.
The input is the complex modulated signal at baseband.
Demodulated packets are sent to the handler.
Args:
options: pass modulation options from higher layers (fft length, occupied tones, etc.)
callback: function of two args: ok, payload (ok: bool; payload: string)
"""
gr.hier_block2.__init__(self, "ofdm_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._rcvd_pktq = gr.msg_queue() # holds packets from the PHY
self._modulation = options.modulation
self._fft_length = options.fft_length
self._occupied_tones = options.occupied_tones
self._cp_length = options.cp_length
self._snr = options.snr
# Use freq domain to get doubled-up known symbol for correlation in time domain
zeros_on_left = int(math.ceil((self._fft_length - self._occupied_tones)/2.0))
ksfreq = known_symbols_4512_3[0:self._occupied_tones]
for i in range(len(ksfreq)):
if((zeros_on_left + i) & 1):
ksfreq[i] = 0
# hard-coded known symbols
preambles = (ksfreq,)
symbol_length = self._fft_length + self._cp_length
self.ofdm_recv = ofdm_receiver(self._fft_length,
self._cp_length,
self._occupied_tones,
self._snr, preambles,
options.log)
mods = {"bpsk": 2, "qpsk": 4, "8psk": 8, "qam8": 8, "qam16": 16, "qam64": 64, "qam256": 256}
arity = mods[self._modulation]
rot = 1
if self._modulation == "qpsk":
rot = (0.707+0.707j)
# FIXME: pass the constellation objects instead of just the points
if(self._modulation.find("psk") >= 0):
constel = psk.psk_constellation(arity)
rotated_const = map(lambda pt: pt * rot, constel.points())
elif(self._modulation.find("qam") >= 0):
constel = qam.qam_constellation(arity)
rotated_const = map(lambda pt: pt * rot, constel.points())
#print rotated_const
phgain = 0.25
frgain = phgain*phgain / 4.0
self.ofdm_demod = digital.ofdm_frame_sink(rotated_const, range(arity),
self._rcvd_pktq,
self._occupied_tones,
phgain, frgain)
self.connect(self, self.ofdm_recv)
self.connect((self.ofdm_recv, 0), (self.ofdm_demod, 0))
self.connect((self.ofdm_recv, 1), (self.ofdm_demod, 1))
# added output signature to work around bug, though it might not be a bad
# thing to export, anyway
self.connect(self.ofdm_recv.chan_filt, self)
if options.log:
self.connect(self.ofdm_demod,
blocks.file_sink(gr.sizeof_gr_complex*self._occupied_tones,
"ofdm_frame_sink_c.dat"))
else:
self.connect(self.ofdm_demod,
blocks.null_sink(gr.sizeof_gr_complex*self._occupied_tones))
if options.verbose:
self._print_verbage()
self._watcher = _queue_watcher_thread(self._rcvd_pktq, callback)
def __init__(
self,
n_bursts, n_channels,
freq_delta, base_freq,
burst_length, base_time, hop_time,
post_tuning=True,
tx_gain=30,
verbose=False
):
gr.hier_block2.__init__(self,
"FrequencyHopperSrc",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex),
)
n_samples_total = n_bursts * burst_length
self.hop_sequence = numpy.arange(base_freq, base_freq + n_channels * freq_delta, freq_delta)
# self.hop_sequence = 2410000000, 2415000000, 2425000000, 2430000000, 2435000000, 2440000000, 2455000000
# numpy.random.shuffle(self.hop_sequence) #this randomly shuffels frequencies in the specified range
# self.hop_sequence = [self.hop_sequence[x % n_channels] for x in xrange(n_bursts)]
self.hop_sequence = [self.hop_sequence[x % 7]for x in xrange(n_bursts)]
if verbose:
print "Hop Frequencies | Hop Pattern"
print "=================|================================"
for f in self.hop_sequence:
print "{:6.3f} MHz | ".format(f/1e6),
if n_channels < 50:
print " " * int((f - base_freq) / freq_delta) + "#"
else:
print "\n"
print "=================|================================"
gain_tag = gr.tag_t()
gain_tag.offset = 0
gain_tag.key = pmt.string_to_symbol('tx_command')
gain_tag.value = pmt.cons(
pmt.intern("gain"),
# These are both valid:
#pmt.from_double(tx_gain)
pmt.cons(pmt.to_pmt(0), pmt.to_pmt(tx_gain))
)
tag_list = [gain_tag,]
for i in xrange(n_bursts):
tune_tag = gr.tag_t()
tune_tag.offset = i * burst_length
if i > 0 and post_tuning:
tune_tag.offset -= 1 # Move it to last sample of previous burst
tune_tag.key = pmt.string_to_symbol('tx_freq')
tune_tag.value = pmt.to_pmt(self.hop_sequence[i])
tag_list.append(tune_tag)
length_tag = gr.tag_t()
length_tag.offset = i * burst_length
length_tag.key = pmt.string_to_symbol('packet_len')
length_tag.value = pmt.from_long(burst_length)
tag_list.append(length_tag)
time_tag = gr.tag_t()
time_tag.offset = i * burst_length
time_tag.key = pmt.string_to_symbol('tx_time')
time_tag.value = pmt.make_tuple(
pmt.from_uint64(int(base_time + i * hop_time)),
pmt.from_double((base_time + i * hop_time) % 1),
)
tag_list.append(time_tag)
tag_source = blocks.vector_source_c((1.0,) * n_samples_total, repeat=False, tags=tag_list)
mult = blocks.multiply_cc()
self.connect(self, mult, self)
self.connect(tag_source, (mult, 1))
def __init__(self,
sign_freq,
audio_freq,
signal_low_pass_cutoff=10000,
signal_low_pass_trans=1000,
audio_low_pass_cutoff=3000,
audio_low_pass_trans=20,
use_dc_blocker=True,
audio_gain=1):
##################################################
# Variables
##################################################
self.sign_freq = sign_freq
self.audio_freq = audio_freq
self.signal_low_pass_cutoff = signal_low_pass_cutoff
self.signal_low_pass_trans = signal_low_pass_trans
self.audio_low_pass_cutoff = audio_low_pass_cutoff
self.audio_low_pass_trans = audio_low_pass_trans
self.use_dc_blocker = use_dc_blocker
self.audio_gain = audio_gain
# hyper parameter
self.low_pass_ampl_bound = 0.1
self.low_pass_window = firdes.WIN_HAMMING
self.low_pass_beta = 6.76
##################################################
# Submodule
##################################################
self.input_resample = filter.rational_resampler_ccf(
interpolation=2000000,
decimation=sign_freq,
taps=None,
fractional_bw=None)
self.signal_low_pass_filter = eewls.auto_gain_low_pass_filter(
filter.fir_filter_ccf, 8, self.low_pass_ampl_bound, 2000000,
self.signal_low_pass_cutoff, self.signal_low_pass_trans,
self.low_pass_window, self.low_pass_beta, str(complex))
self.am_demod = analog.am_demod_cf(channel_rate=50000,
audio_decim=5,
audio_pass=5000,
audio_stop=5500)
self.resampler = filter.rational_resampler_fff(
interpolation=48 * self.audio_freq * 2 / 96000,
decimation=50,
taps=None,
fractional_bw=None)
self.audio_filter = filter.interp_fir_filter_fff(
1,
firdes.low_pass(self.audio_gain, self.audio_freq * 2,
self.audio_low_pass_cutoff,
self.audio_low_pass_trans, self.low_pass_window,
self.low_pass_beta))
gr.hier_block2.__init__(
self, "fm_audio_decoder",
gr.io_signature(
1, 1,
self.input_resample.input_signature().sizeof_stream_item(0)),
gr.io_signature(
1, 1,
self.audio_filter.output_signature().sizeof_stream_item(0)))
if self.use_dc_blocker:
self.dc_blocker = filter.dc_blocker_cc(256, True)
##################################################
# Connections
##################################################
self.connect((self, 0), (self.input_resample, 0))
self.connect((self.input_resample, 0),
(self.signal_low_pass_filter, 0))
if self.use_dc_blocker:
self.connect((self.signal_low_pass_filter, 0),
(self.dc_blocker, 0))
self.connect((self.dc_blocker, 0), (self.am_demod, 0))
else:
self.connect((self.signal_low_pass_filter, 0), (self.am_demod, 0))
self.connect((self.am_demod, 0), (self.resampler, 0))
self.connect((self.resampler, 0), (self.audio_filter, 0))
self.connect((self.audio_filter, 0), (self, 0))
def __init__(self, magnitude=0, phase=0, mode=0):
'''
This block implements the single branch IQ imbalance
transmitter and receiver models.
Developed from source (2014):
"In-Phase and Quadrature Imbalance:
Modeling, Estimation, and Compensation"
TX Impairment:
{R}--|Multiply: 10**(mag/20)|--+--|Multiply: cos(pi*degree/180)|--X1
Input ---|Complex2Float|---| +--|Multiply: sin(pi*degree/180)|--X2
{I}--| Adder |
X2--| (+) |--X3
X1--{R}--| Float 2 |--- Output
X3--{I}--| Complex |
RX Impairment:
{R}--|Multiply: cos(pi*degree/180)|-------| |
Input ---|Complex2Float|---| | Adder |--X1
{I}--+--|Multiply: sin(pi*degree/180)|----| (+) |
|
+--X2
X1--|Multiply: 10**(mag/20)|--{R}--| Float 2 |--- Output
X2---------------------------{I}--| Complex |
(ASCII ART monospace viewing)
'''
gr.hier_block2.__init__(
self,
"IQ Imbalance Generator",
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
)
##################################################
# Parameters
##################################################
self.magnitude = magnitude
self.phase = phase
self.mode = mode
##################################################
# Blocks
##################################################
# Same blocks for Transmitter and Receiver
self.mag = blocks.multiply_const_vff((math.pow(10,
magnitude / 20.0), ))
self.sin_phase = blocks.multiply_const_vff(
(math.sin(phase * math.pi / 180.0), ))
self.cos_phase = blocks.multiply_const_vff(
(math.cos(phase * math.pi / 180.0), ))
self.f2c = blocks.float_to_complex(1)
self.c2f = blocks.complex_to_float(1)
self.adder = blocks.add_vff(1)
##################################################
# Connections
##################################################
if (self.mode):
# Receiver Mode
self.connect((self, 0), (self.c2f, 0))
self.connect((self.c2f, 0), (self.cos_phase, 0))
self.connect((self.cos_phase, 0), (self.adder, 0))
self.connect((self.c2f, 1), (self.sin_phase, 0))
self.connect((self.sin_phase, 0), (self.adder, 1))
self.connect((self.adder, 0), (self.mag, 0))
self.connect((self.mag, 0), (self.f2c, 0))
self.connect((self.c2f, 1), (self.f2c, 1))
self.connect((self.f2c, 0), (self, 0))
else:
# Transmitter Mode
self.connect((self, 0), (self.c2f, 0))
self.connect((self.c2f, 0), (self.mag, 0))
self.connect((self.mag, 0), (self.cos_phase, 0))
self.connect((self.cos_phase, 0), (self.f2c, 0))
self.connect((self.mag, 0), (self.sin_phase, 0))
self.connect((self.sin_phase, 0), (self.adder, 0))
self.connect((self.c2f, 1), (self.adder, 1))
self.connect((self.adder, 0), (self.f2c, 1))
self.connect((self.f2c, 0), (self, 0))
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
excess_bw=_def_excess_bw,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for RRC-filtered QPSK modulation.
The input is a byte stream (unsigned char) and the
output is the complex modulated signal at baseband.
@param samples_per_symbol: samples per symbol >= 2
@type samples_per_symbol: integer
@param excess_bw: Root-raised cosine filter excess bandwidth
@type excess_bw: float
@param verbose: Print information about modulator?
@type verbose: bool
@param debug: Print modualtion data to files?
@type debug: bool
"""
gr.hier_block2.__init__(
self,
"cqpsk_mod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._samples_per_symbol = samples_per_symbol
self._excess_bw = excess_bw
if not isinstance(samples_per_symbol, int) or samples_per_symbol < 2:
raise TypeError, ("sbp must be an integer >= 2, is %d" %
samples_per_symbol)
ntaps = 11 * samples_per_symbol
arity = 8
# turn bytes into k-bit vectors
self.bytes2chunks = \
blocks.packed_to_unpacked_bb(self.bits_per_symbol(), gr.GR_MSB_FIRST)
# 0 +45 1 [+1]
# 1 +135 3 [+3]
# 2 -45 7 [-1]
# 3 -135 5 [-3]
self.pi4map = [1, 3, 7, 5]
self.symbol_mapper = digital.map_bb(self.pi4map)
self.diffenc = digital.diff_encoder_bb(arity)
self.chunks2symbols = digital.chunks_to_symbols_bc(
psk.constellation[arity])
# pulse shaping filter
self.rrc_taps = filter.firdes.root_raised_cosine(
self.
_samples_per_symbol, # gain (sps since we're interpolating by sps)
self._samples_per_symbol, # sampling rate
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = filter.interp_fir_filter_ccf(
self._samples_per_symbol, self.rrc_taps)
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Connect & Initialize base class
self.connect(self, self.bytes2chunks, self.symbol_mapper, self.diffenc,
self.chunks2symbols, self.rrc_filter, self)
def __init__(self):
gr.hier_block2.__init__(
self,
"bch_viterbi_vfvb",
gr.io_signature(1, 1, gr.sizeof_float * 120), # Input signature
gr.io_signature(1, 1, gr.sizeof_char * 40)) # Output signature
# Define blocks and connect them
# Repeat input vector one time to get viterbi decoder state right (tail-biting stuff)
#self.rpt = blocks.repeat(gr.sizeof_float * 120, 2)
# viterbi decoder requires stream as input
#self.vtos = blocks.vector_to_stream(1 * gr.sizeof_float, 120)
# self.vtss = blocks.vector_to_streams(1* gr.sizeof_float, 120, "bch_viterbi_vector_to_streams_0")
self.vtss = blocks.vector_to_streams(1 * gr.sizeof_float, 120)
#self.app = blocks.streams_to_stream(1* gr.sizeof_float, 138, "bch_viterbi_streams_to_stream_0")
self.app = blocks.streams_to_stream(1 * gr.sizeof_float, 138)
self.connect(self, self.vtss)
for i in range(18):
self.connect((self.vtss, 120 - 18 + i), (self.app, i))
for i in range(120):
self.connect((self.vtss, i), (self.app, i + 18))
# Correct FSM instantiation: k=num_input_bits, n=num_output_bits, Tuple[dim(k*n)] (decimal notation)
self.fsm = trellis.fsm(1, 3, [91, 121, 117])
# Values for viterbi decoder
K = 46 # steps for one coding block
SO = 0 # initial state
SK = -1 # final state (in this case unknown, therefore -1)
D = 3 # dimensionality
# D = 3 follows from the fact that 1 {0,1} input symbol of the encoder produces 3 {0,1} output symbols.
# (packed into one byte {0,1,...,7} )
# with NRZ coding follows:
# 0 --> 1
# 1 --> -1
# This leads to the following constellation input
# | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
constellation = [
1, 1, 1, 1, 1, -1, 1, -1, 1, 1, -1, -1, -1, 1, 1, -1, 1, -1, -1,
-1, 1, -1, -1, -1
]
# print "len(constellation)/D = " + str(len(constellation)/D) + "\tfsm.O = " + str(self.fsm.O())
# Viterbi_combined input: FSM, K, SO, SK, D, TABLE, TYPE
# FSM = Finite State Machine
# K = number of output symbols produced by the FSM
# SO = initial state of the FSM
# SK = final state of the FSM (unknown in this example)
# D = dimensionality
# TABLE = constellation of the input symbols
# self.vit = trellis.viterbi_combined_fb(self.fsm, K, SO, SK, D, constellation, 200, "bch_viterbi_combined_fb_0")
self.vit = trellis.viterbi_combined_fb(self.fsm, K, SO, SK, D,
constellation, 200)
self.connect(self.app, self.vit)
# connect all streams which are crated yet
#self.connect(self,self.rpt,self.vtos,self.vit)
# self.keep = blocks.keep_m_in_n(gr.sizeof_char, 40, 46, 6, "bch_viterbi_keep_m_in_n_0")
self.keep = blocks.keep_m_in_n(gr.sizeof_char, 40, 46, 6)
# self.tovec = blocks.stream_to_vector(1, 40, "bch_viterbi_stream_to_vector_0")
self.tovec = blocks.stream_to_vector(1, 40)
self.connect(self.vit, self.keep, self.tovec, self)
def __init__(self,
baudrate,
samp_rate,
iq,
deviation=None,
subaudio=False,
dc_block=True,
dump_path=None,
options=None):
gr.hier_block2.__init__(
self, "fsk_demodulator",
gr.io_signature(1, 1,
gr.sizeof_gr_complex if iq else gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_float))
options_block.__init__(self, options)
use_agc = self.options.use_agc or not iq
if dump_path is not None:
dump_path = pathlib.Path(dump_path)
if deviation is not None:
_deviation = deviation
else:
_deviation = self.options.deviation
if iq:
self.demod = analog.quadrature_demod_cf(samp_rate /
(2 * pi * _deviation))
self.connect(self, self.demod)
else:
self.demod = self
sps = samp_rate / baudrate
max_sps = 10
if sps > max_sps:
decimation = ceil(sps / max_sps)
else:
decimation = 1
sps /= decimation
if subaudio:
# some not-so-bad filter parameters for subaudio processing
subaudio_cutoff = 2.0 / 3.0 * baudrate
subaudio_transition = subaudio_cutoff / 4.0
subaudio_taps = firdes.low_pass(1, samp_rate, subaudio_cutoff,
subaudio_transition)
self.subaudio_lowpass = filter.fir_filter_fff(1, subaudio_taps)
# square pulse filter
sqfilter_len = int(samp_rate / baudrate)
taps = np.ones(sqfilter_len) / sqfilter_len
self.lowpass = filter.fir_filter_fff(decimation, taps)
if dc_block:
self.dcblock = filter.dc_blocker_ff(ceil(sps * 32), True)
else:
self.dcblock = self.lowpass # to simplify connections below
if use_agc:
agc_constant = 2e-2 / sps # This gives a time constant of 50 symbols
self.agc = rms_agc_f(agc_constant, 1)
if dump_path is not None:
self.waveform = blocks.file_sink(gr.sizeof_float,
str(dump_path / 'waveform.f32'))
ted_gain = 1.47 # "empiric" formula for TED gain of Gardner detector 1.47 symbol^{-1}
damping = 1.0
self.clock_recovery = digital.symbol_sync_ff(
digital.TED_GARDNER, sps, self.options.clk_bw, damping, ted_gain,
self.options.clk_limit * sps, 1,
digital.constellation_bpsk().base(), digital.IR_PFB_NO_MF)
if dump_path is not None:
self.clock_recovery_out = blocks.file_sink(
gr.sizeof_float, str(dump_path / 'clock_recovery_out.f32'),
False)
self.clock_recovery_err = blocks.file_sink(
gr.sizeof_float, str(dump_path / 'clock_recovery_err.f32'),
False)
self.clock_recovery_T_inst = blocks.file_sink(
gr.sizeof_float, str(dump_path / 'clock_recovery_T_inst.f32'),
False)
self.clock_recovery_T_avg = blocks.file_sink(
gr.sizeof_float, str(dump_path / 'clock_recovery_T_avg.f32'),
False)
self.connect(self.clock_recovery, self.clock_recovery_out)
self.connect((self.clock_recovery, 1), self.clock_recovery_err)
self.connect((self.clock_recovery, 2), self.clock_recovery_T_inst)
self.connect((self.clock_recovery, 3), self.clock_recovery_T_avg)
conns = [self.demod]
if subaudio:
conns.append(self.subaudio_lowpass)
conns.append(self.lowpass)
if dc_block:
conns.append(self.dcblock)
self.connect(*conns)
if use_agc:
self.connect(self.dcblock, self.agc, self.clock_recovery)
if dump_path is not None:
self.connect(self.agc, self.waveform)
else:
self.connect(self.dcblock, self.clock_recovery)
if dump_path is not None:
self.connect(self.dcblock, self.waveform)
self.connect(self.clock_recovery, self)
def __init__(self, fft_length, cp_length, carrier_num, 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 = blocks.add_const_cc(0)
# PN Sync
# Create a delay line
self.delay = blocks.delay(gr.sizeof_gr_complex, fft_length/2)
# Correlation from ML Sync
self.conjg = blocks.conjugate_cc();
self.corr = blocks.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 = filter.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 = filter.fft_filter_ccc(1,moving_sum_taps)
# Create a moving sum filter for the input
self.inputmag2 = blocks.complex_to_mag_squared()
movingsum2_taps = [1.0 for i in range(fft_length//2)]
if 1:
self.inputmovingsum = filter.fir_filter_fff(1,movingsum2_taps)
else:
self.inputmovingsum = filter.fft_filter_fff(1,movingsum2_taps)
self.square = blocks.multiply_ff()
self.normalize = blocks.divide_ff()
# Get magnitude (peaks) and angle (phase/freq error)
self.c2mag = blocks.complex_to_mag_squared()
self.angle = blocks.complex_to_arg()
self.sample_and_hold = gr_papyrus.sample_and_hold_ff()
#ML measurements input to sampler block and detect
self.sub1 = blocks.add_const_ff(-1)
# linklab, change peak detector parameters: use higher threshold to detect rise/fall of peak
#self.pk_detect = gr.peak_detector_fb(0.20, 0.20, 30, 0.001)
self.pk_detect = gr_papyrus.peak_detector_fb(0.50, 0.60, 30, 0.001, carrier_num) # linklab
#self.pk_detect = gr.peak_detector2_fb(9)
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))
# Get the power of the input signal to normalize the output of the correlation
self.connect(self.input, self.inputmag2, self.inputmovingsum)
self.connect(self.inputmovingsum, (self.square,0))
self.connect(self.inputmovingsum, (self.square,1))
self.connect(self.square, (self.normalize,1))
self.connect(self.c2mag, (self.normalize,0))
# Create a moving sum filter for the corr output
matched_filter_taps = [1.0/cp_length for i in range(cp_length)]
self.matched_filter = filter.fir_filter_fff(1,matched_filter_taps)
self.connect(self.normalize, self.matched_filter)
# linklab, provide the signal power into peak detector, linklab
self.connect(self.square, (self.pk_detect,1))
#self.connect(self.matched_filter, self.sub1, self.pk_detect)
self.connect(self.matched_filter, self.sub1, (self.pk_detect, 0))
#self.connect(self.matched_filter, self.pk_detect)
self.connect(self.pk_detect, (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))
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, k, cl_loop_bandwidth, cl_order, cl_freq_sub, ss_sps,
ss_loop_bandwidth, ss_ted_gain, ss_damping, ss_max_dev,
ss_out_ss, ss_interpolation, ss_ted_type, ss_constellation,
ss_nfilter, ss_pfb_mf_taps, sel_costas, sel_spl, samp_rate):
gr.hier_block2.__init__(
self,
"demodulator",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
##################################################
# Variables
##################################################
self.k = k
self.cl_loop_bandwidth = cl_loop_bandwidth
self.cl_order = cl_order
self.cl_freq_sub = cl_freq_sub
self.ss_sps = ss_sps
self.ss_loop_bandwidth = ss_loop_bandwidth
self.ss_ted_gain = ss_ted_gain
self.ss_damping = ss_damping
self.ss_max_dev = ss_max_dev
self.ss_out_ss = ss_out_ss
self.ss_interpolation = ss_interpolation
self.ss_ted_type = ss_ted_type
self.ss_constellation = ss_constellation
self.ss_nfilter = ss_nfilter
self.ss_pfb_mf_taps = ss_pfb_mf_taps
self.sel_costas = sel_costas
self.sel_spl = sel_spl
self.samp_rate = samp_rate
##################################################
# Blocks
##################################################
self.digital_sync = digital.symbol_sync_ff(
self.ss_ted_type, self.ss_sps, self.ss_loop_bandwidth,
self.ss_damping, self.ss_ted_gain, self.ss_max_dev, self.ss_out_ss,
self.ss_constellation, self.ss_interpolation, self.ss_nfilter,
(self.ss_pfb_mf_taps))
self.spl_decoder = ecss.spl_decoder()
self.costas_loop_cc = digital.costas_loop_cc(self.cl_loop_bandwidth,
self.cl_order, False)
self.signal_gen = analog.sig_source_c(samp_rate, analog.GR_SIN_WAVE,
self.cl_freq_sub, 1, 0)
self.multiply = blocks.multiply_vcc(1)
self.hilbert = filter.hilbert_fc(65, firdes.WIN_HAMMING, 6.76)
self.null_complex = blocks.null_sink(gr.sizeof_gr_complex * 1)
self.null_float = blocks.null_sink(gr.sizeof_float * 1)
self.to_char = blocks.float_to_uchar()
self.unpack = blocks.unpack_k_bits_bb(k)
##################################################
# Connections
##################################################
if (sel_costas == 0):
# if (type == 0):
# self.connect(self, (self.multiply, 0))
# else:
self.connect(self, self.hilbert, (self.multiply, 0))
self.connect(self.signal_gen, (self.multiply, 1))
self.connect(self.multiply, self.costas_loop_cc)
self.connect((self.costas_loop_cc, 0), self.null_complex)
self.connect((self.costas_loop_cc, 1), self.null_float)
self.connect((self.costas_loop_cc, 2), self.digital_sync)
else:
self.connect(self, self.digital_sync)
if (sel_spl == 0):
self.connect(self.digital_sync, self.spl_decoder, self.unpack,
self)
else:
self.connect(self.digital_sync, self.to_char, self.unpack, self)
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
excess_bw=_def_excess_bw,
costas_alpha=_def_costas_alpha,
gain_mu=_def_gain_mu,
mu=_def_mu,
omega_relative_limit=_def_omega_relative_limit,
gray_code=_def_gray_code,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for RRC-filtered CQPSK demodulation
The input is the complex modulated signal at baseband.
The output is a stream of floats in [ -3 / -1 / +1 / +3 ]
@param samples_per_symbol: samples per symbol >= 2
@type samples_per_symbol: float
@param excess_bw: Root-raised cosine filter excess bandwidth
@type excess_bw: float
@param costas_alpha: loop filter gain
@type costas_alphas: float
@param gain_mu: for M&M block
@type gain_mu: float
@param mu: for M&M block
@type mu: float
@param omega_relative_limit: for M&M block
@type omega_relative_limit: float
@param gray_code: Tell modulator to Gray code the bits
@type gray_code: bool
@param verbose: Print information about modulator?
@type verbose: bool
@param debug: Print modualtion data to files?
@type debug: bool
"""
gr.hier_block2.__init__(
self,
"cqpsk_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self._samples_per_symbol = samples_per_symbol
self._excess_bw = excess_bw
self._costas_alpha = costas_alpha
self._mm_gain_mu = gain_mu
self._mm_mu = mu
self._mm_omega_relative_limit = omega_relative_limit
self._gray_code = gray_code
if samples_per_symbol < 2:
raise TypeError, "sbp must be >= 2, is %d" % samples_per_symbol
arity = pow(2, self.bits_per_symbol())
# Automatic gain control
scale = (1.0 / 16384.0)
self.pre_scaler = blocks.multiply_const_cc(
scale) # scale the signal from full-range to +-1
#self.agc = gr.agc2_cc(0.6e-1, 1e-3, 1, 1, 100)
self.agc = analog.feedforward_agc_cc(16, 2.0)
# RRC data filter
ntaps = 11 * samples_per_symbol
self.rrc_taps = filter.firdes.root_raised_cosine(
1.0, # gain
self._samples_per_symbol, # sampling rate
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = filter.interp_fir_filter_ccf(1, self.rrc_taps)
if not self._mm_gain_mu:
sbs_to_mm = {
2: 0.050,
3: 0.075,
4: 0.11,
5: 0.125,
6: 0.15,
7: 0.15
}
self._mm_gain_mu = sbs_to_mm[samples_per_symbol]
self._mm_omega = self._samples_per_symbol
self._mm_gain_omega = .25 * self._mm_gain_mu * self._mm_gain_mu
self._costas_beta = 0.25 * self._costas_alpha * self._costas_alpha
fmin = -0.025
fmax = 0.025
self.receiver = digital.mpsk_receiver_cc(arity, pi / 4.0, 2 * pi / 150,
fmin, fmax, self._mm_mu,
self._mm_gain_mu,
self._mm_omega,
self._mm_gain_omega,
self._mm_omega_relative_limit)
self.receiver.set_alpha(self._costas_alpha)
self.receiver.set_beta(self._costas_beta)
# Perform Differential decoding on the constellation
self.diffdec = digital.diff_phasor_cc()
# take angle of the difference (in radians)
self.to_float = blocks.complex_to_arg()
# convert from radians such that signal is in -3/-1/+1/+3
self.rescale = blocks.multiply_const_ff(1 / (pi / 4))
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Connect & Initialize base class
self.connect(self, self.pre_scaler, self.agc, self.rrc_filter,
self.receiver, self.diffdec, self.to_float, self.rescale,
self)
def __init__(self,
dab_params,
bit_rate,
address,
subch_size,
protection,
output_float,
verbose=False,
debug=False):
if output_float: # map short samples to the range [-1,1] in floats
gr.hier_block2.__init__(
self,
"dabplus_audio_decoder_ff",
# Input signature
gr.io_signature(1, 1,
gr.sizeof_float * dab_params.num_carriers * 2),
# Output signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_float))
else: # output signed 16 bit integers (directly from decoder)
gr.hier_block2.__init__(
self,
"dabplus_audio_decoder_ff",
# Input signature
gr.io_signature(1, 1,
gr.sizeof_float * dab_params.num_carriers * 2),
# Output signature
gr.io_signature2(2, 2, gr.sizeof_short, gr.sizeof_short))
self.dp = dab_params
self.bit_rate_n = bit_rate / 8
self.address = address
self.size = subch_size
self.protection = protection
self.output_float = output_float
self.verbose = verbose
self.debug = debug
# sanity check
# if self.bit_rate_n*6 != self.size:
# log = gr.logger("log")
# log.debug("bit rate and subchannel size are not fitting")
# log.set_level("ERROR")
# raise ValueError
# MSC decoder extracts logical frames out of transmission frame and decodes it
self.msc_decoder = grdab.msc_decode(self.dp, self.address, self.size,
self.protection, self.verbose,
self.debug)
# firecode synchronizes to superframes and checks
self.firecode = grdab.firecode_check_bb_make(self.bit_rate_n)
# Reed-Solomon error repair
self.rs = grdab.reed_solomon_decode_bb_make(self.bit_rate_n)
# mp4 decoder
self.mp4 = grdab.mp4_decode_bs_make(self.bit_rate_n)
self.connect((self, 0), self.msc_decoder, self.firecode, self.rs,
self.mp4)
if self.output_float:
# map short samples to the range [-1,1] in floats
self.s2f_left = blocks.short_to_float_make(1, 32767)
self.s2f_right = blocks.short_to_float_make(1, 32767)
self.gain_left = blocks.multiply_const_ff(1, 1)
self.gain_right = blocks.multiply_const_ff(1, 1)
self.connect((self.mp4, 0), self.s2f_left, self.gain_left,
(self, 0))
self.connect((self.mp4, 1), self.s2f_right, self.gain_right,
(self, 1))
else:
# output signed 16 bit integers (directly from decoder)
self.connect((self.mp4, 0), (self, 0))
self.connect((self.mp4, 1), (self, 1))
def __init__(self, options, payload='', msgq_limit=2, pad_for_usrp=False):
"""
Hierarchical block for sending packets
Packets to be sent are enqueued by calling send_pkt.
The output is the complex modulated signal at baseband.
@param options: pass modulation options from higher layers (fft length, occupied tones, etc.)
@param msgq_limit: maximum number of messages in message queue
@type msgq_limit: int
@param pad_for_usrp: If true, packets are padded such that they end up a multiple of 128 samples
"""
gr.hier_block2.__init__(
self,
"ofdm_mod",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._fft_length = 64
self._total_sub_carriers = 53
self._data_subcarriers = 48
self._cp_length = 16
self._regime = options.regime
self._symbol_length = self._fft_length + self._cp_length
self._role = options.role
# assuming we have 100Ms/s going to the USRP2 and 80 samples per symbol
# we can calculate the OFDM symboltime (in microseconds)
# depending on the interpolation factor
self._symbol_time = options.interp * (self._fft_length +
self._cp_length) / 100
win = []
if (self._regime == "1" or self._regime == "2"):
rotated_const = ofdm_packet_utils.bpsk(self)
elif (self._regime == "3" or self._regime == "4"):
rotated_const = ofdm_packet_utils.qpsk(self)
elif (self._regime == "5" or self._regime == "6"):
rotated_const = ofdm_packet_utils.qam16(self)
elif (self._regime == "7" or self._regime == "8"):
rotated_const = ofdm_packet_utils.qam64(self)
# map groups of bits to complex symbols
self._pkt_input = ftw.ofdm_mapper(rotated_const, msgq_limit,
self._data_subcarriers,
self._fft_length)
# insert pilot symbols (use pnc block * by lzyou)
if self._role == 'A':
print " >>> [FPNC]: *A* Insert Pilot"
self.pilot = ftw.pnc_ofdm_pilot_cc(self._data_subcarriers, 1)
elif self._role == 'B':
print " >>> [FPNC]: *B* Insert Pilot"
self.pilot = ftw.pnc_ofdm_pilot_cc(self._data_subcarriers, 2)
else:
print " >>> [FTW ]: Insert Pilot"
self.pilot = ftw.ofdm_pilot_cc(self._data_subcarriers)
# just for test
#self.pilot = ftw.pnc_ofdm_pilot_cc(self._data_subcarriers, 1)
#self.pilot = ftw.pnc_ofdm_pilot_cc(self._data_subcarriers, 2)
# move subcarriers to their designated place and insert DC
self.cmap = ftw.ofdm_cmap_cc(self._fft_length,
self._total_sub_carriers)
# inverse fast fourier transform
self.ifft = gr.fft_vcc(self._fft_length, False, win, False)
# add cyclic prefix
from gnuradio import digital
self.cp_adder = digital.ofdm_cyclic_prefixer(self._fft_length,
self._symbol_length)
self.connect(
gr.null_source(gr.sizeof_char),
(self.cp_adder,
1)) # Note: dirty modification to accomdate the API change
# scale accordingly
self.scale = gr.multiply_const_cc(1.0 / math.sqrt(self._fft_length))
# we need to know the number of OFDM data symbols for preamble and zerogap
info = ofdm_packet_utils.get_info(payload, options.regime,
self._symbol_time)
N_sym = info["N_sym"]
# add training sequence (modify by lzyou)
if self._role == 'A':
print " >>> [FPNC]: *A* Insert Preamble"
self.preamble = ofdm_packet_utils.insert_preamble(
self._symbol_length, N_sym, 'A')
elif self._role == 'B':
print " >>> [FPNC]: *B* Insert Preamble"
self.preamble = ofdm_packet_utils.insert_preamble(
self._symbol_length, N_sym, 'B')
else:
print " >>> [FTW ]: Insert Preamble"
self.preamble = ofdm_packet_utils.insert_preamble(
self._symbol_length, N_sym)
# append zero samples at the end (receiver needs that to decode)
if self._role == None:
print " >>> [FTW ]: Insert Zerogap"
self.zerogap = ofdm_packet_utils.insert_zerogap(
self._symbol_length, N_sym)
else:
print " >>> [FPNC]: Insert Zerogap"
self.zerogap = ofdm_packet_utils.insert_zerogap(
self._symbol_length, N_sym, 'FPNC')
self.s2v = gr.stream_to_vector(gr.sizeof_gr_complex,
self._symbol_length)
self.v2s = gr.vector_to_stream(gr.sizeof_gr_complex,
self._symbol_length)
# swap real and immaginary component before sending (GNURadio/USRP2 bug!)
if options.swapIQ == True:
self.gr_complex_to_imag_0 = gr.complex_to_imag(1)
self.gr_complex_to_real_0 = gr.complex_to_real(1)
self.gr_float_to_complex_0 = gr.float_to_complex(1)
self.connect((self.v2s, 0), (self.gr_complex_to_imag_0, 0))
self.connect((self.v2s, 0), (self.gr_complex_to_real_0, 0))
self.connect((self.gr_complex_to_real_0, 0),
(self.gr_float_to_complex_0, 1))
self.connect((self.gr_complex_to_imag_0, 0),
(self.gr_float_to_complex_0, 0))
self.connect((self.gr_float_to_complex_0, 0), (self))
elif options.swapIQ == False:
self.gr_complex_to_imag_0 = gr.complex_to_imag(1)
self.gr_complex_to_real_0 = gr.complex_to_real(1)
self.gr_float_to_complex_0 = gr.float_to_complex(1)
self.connect((self.v2s, 0), (self.gr_complex_to_imag_0, 0))
self.connect((self.v2s, 0), (self.gr_complex_to_real_0, 0))
self.connect((self.gr_complex_to_imag_0, 0),
(self.gr_float_to_complex_0, 1))
self.connect((self.gr_complex_to_real_0, 0),
(self.gr_float_to_complex_0, 0))
self.connect((self.gr_float_to_complex_0, 0), (self))
# connect the blocks
self.connect((self._pkt_input, 0), (self.pilot, 0))
self.connect((self._pkt_input, 1), (self.preamble, 1))
self.connect((self.preamble, 1), (self.zerogap, 1))
self.connect(self.pilot, self.cmap, self.ifft, self.cp_adder,
self.scale, self.s2v, self.preamble, self.zerogap,
self.v2s)
if options.log:
self.connect(
(self._pkt_input),
gr.file_sink(gr.sizeof_gr_complex * self._data_subcarriers,
"ofdm_mapper.dat"))
self.connect(
self.pilot,
gr.file_sink(
gr.sizeof_gr_complex * (5 + self._data_subcarriers),
"ofdm_pilot.dat"))
self.connect(
self.cmap,
gr.file_sink(gr.sizeof_gr_complex * self._fft_length,
"ofdm_cmap.dat"))
self.connect(
self.ifft,
gr.file_sink(gr.sizeof_gr_complex * self._fft_length,
"ofdm_ifft.dat"))
self.connect(
self.cp_adder,
gr.file_sink(gr.sizeof_gr_complex, "ofdm_cp_adder.dat"))
self.connect(self.scale,
gr.file_sink(gr.sizeof_gr_complex, "ofdm_scale.dat"))
self.connect(
self.preamble,
gr.file_sink(gr.sizeof_gr_complex * self._symbol_length,
"ofdm_preamble.dat"))
self.connect(
self.zerogap,
gr.file_sink(gr.sizeof_gr_complex * self._symbol_length,
"ofdm_zerogap.dat"))
def __init__(
self,
parent,
x_offset=0,
ref_level=50,
#sample_rate=1,
data_len=512 * 2,
#fft_rate=waterfall_window.DEFAULT_FRAME_RATE,
#average=False,
#avg_alpha=None,
title='',
size=waterfall_window.DEFAULT_WIN_SIZE,
ref_scale=2.0,
dynamic_range=80,
num_lines=256,
win=None,
always_run=False,
**kwargs #do not end with a comma
):
#ensure avg alpha
#if avg_alpha is None: avg_alpha = 2.0/fft_rate
#init
gr.hier_block2.__init__(
self,
"waterfall_sink",
gr.io_signature(1, 1, gr.sizeof_float * data_len),
gr.io_signature(0, 0, 0),
)
#blocks
msgq = gr.msg_queue(2)
sink = blocks.message_sink(gr.sizeof_float * data_len, msgq, True)
#controller
self.controller = pubsub()
#start input watcher
common.input_watcher(msgq, self.controller, MSG_KEY)
#create window
self.win = waterfall_window.waterfall_window(
parent=parent,
controller=self.controller,
size=size,
title=title,
data_len=data_len,
num_lines=num_lines,
x_offset=x_offset,
#decimation_key=DECIMATION_KEY,
#sample_rate_key=SAMPLE_RATE_KEY,
#frame_rate_key=FRAME_RATE_KEY,
dynamic_range=dynamic_range,
ref_level=ref_level,
#average_key=AVERAGE_KEY,
#avg_alpha_key=AVG_ALPHA_KEY,
msg_key=MSG_KEY,
)
common.register_access_methods(self, self.win)
setattr(self.win, 'set_baseband_freq',
getattr(self, 'set_baseband_freq')) #BACKWARDS # FIXME
#connect
if always_run:
connect_fn = self.connect
else:
connect_fn = self.wxgui_connect
connect_fn(self, sink)
def __init__(self, demod_rate, audio_decimation):
"""
Hierarchical block for demodulating a broadcast FM signal.
The input is the downconverted complex baseband signal
(gr_complex). The output is two streams of the demodulated
audio (float) 0=Left, 1=Right.
Args:
demod_rate: input sample rate of complex baseband input. (float)
audio_decimation: how much to decimate demod_rate to get to audio. (integer)
"""
gr.hier_block2.__init__(
self,
"wfm_rcv_fmdet",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(2, 2, gr.sizeof_float)) # Output signature
lowfreq = -125e3 / demod_rate
highfreq = 125e3 / demod_rate
audio_rate = demod_rate / audio_decimation
# We assign to self so that outsiders can grab the demodulator
# if they need to. E.g., to plot its output.
#
# input: complex; output: float
self.fm_demod = analog.fmdet_cf(demod_rate, lowfreq, highfreq, 0.05)
# input: float; output: float
self.deemph_Left = fm_deemph(audio_rate)
self.deemph_Right = fm_deemph(audio_rate)
# compute FIR filter taps for audio filter
width_of_transition_band = audio_rate / 32
audio_coeffs = filter.firdes.low_pass(
1.0, # gain
demod_rate, # sampling rate
15000,
width_of_transition_band,
filter.firdes.WIN_HAMMING)
# input: float; output: float
self.audio_filter = filter.fir_filter_fff(audio_decimation,
audio_coeffs)
if 1:
# Pick off the stereo carrier/2 with this filter. It
# attenuated 10 dB so apply 10 dB gain We pick off the
# negative frequency half because we want to base band by
# it!
## NOTE THIS WAS HACKED TO OFFSET INSERTION LOSS DUE TO
## DEEMPHASIS
stereo_carrier_filter_coeffs = \
filter.firdes.complex_band_pass(10.0,
demod_rate,
-19020,
-18980,
width_of_transition_band,
filter.firdes.WIN_HAMMING)
#print "len stereo carrier filter = ",len(stereo_carrier_filter_coeffs)
#print "stereo carrier filter ", stereo_carrier_filter_coeffs
#print "width of transition band = ",width_of_transition_band, " audio rate = ", audio_rate
# Pick off the double side band suppressed carrier
# Left-Right audio. It is attenuated 10 dB so apply 10 dB
# gain
stereo_dsbsc_filter_coeffs = \
filter.firdes.complex_band_pass(20.0,
demod_rate,
38000-15000 / 2,
38000+15000 / 2,
width_of_transition_band,
filter.firdes.WIN_HAMMING)
#print "len stereo dsbsc filter = ",len(stereo_dsbsc_filter_coeffs)
#print "stereo dsbsc filter ", stereo_dsbsc_filter_coeffs
# construct overlap add filter system from coefficients
# for stereo carrier
self.stereo_carrier_filter = \
filter.fir_filter_fcc(audio_decimation,
stereo_carrier_filter_coeffs)
# carrier is twice the picked off carrier so arrange to do
# a complex multiply
self.stereo_carrier_generator = blocks.multiply_cc()
# Pick off the rds signal
stereo_rds_filter_coeffs = \
filter.firdes.complex_band_pass(30.0,
demod_rate,
57000 - 1500,
57000 + 1500,
width_of_transition_band,
filter.firdes.WIN_HAMMING)
#print "len stereo dsbsc filter = ",len(stereo_dsbsc_filter_coeffs)
#print "stereo dsbsc filter ", stereo_dsbsc_filter_coeffs
# construct overlap add filter system from coefficients for stereo carrier
self.rds_signal_filter = \
filter.fir_filter_fcc(audio_decimation,
stereo_rds_filter_coeffs)
self.rds_carrier_generator = blocks.multiply_cc()
self.rds_signal_generator = blocks.multiply_cc()
self_rds_signal_processor = blocks.null_sink(gr.sizeof_gr_complex)
loop_bw = 2 * math.pi / 100.0
max_freq = -2.0 * math.pi * 18990 / audio_rate
min_freq = -2.0 * math.pi * 19010 / audio_rate
self.stereo_carrier_pll_recovery = analog.pll_refout_cc(
loop_bw, max_freq, min_freq)
#self.stereo_carrier_pll_recovery.squelch_enable(False)
##pll_refout does not have squelch yet, so disabled for
#now
# set up mixer (multiplier) to get the L-R signal at
# baseband
self.stereo_basebander = blocks.multiply_cc()
# pick off the real component of the basebanded L-R
# signal. The imaginary SHOULD be zero
self.LmR_real = blocks.complex_to_real()
self.Make_Left = blocks.add_ff()
self.Make_Right = blocks.sub_ff()
self.stereo_dsbsc_filter = \
filter.fir_filter_fcc(audio_decimation,
stereo_dsbsc_filter_coeffs)
if 1:
# send the real signal to complex filter to pick off the
# carrier and then to one side of a multiplier
self.connect(self, self.fm_demod, self.stereo_carrier_filter,
self.stereo_carrier_pll_recovery,
(self.stereo_carrier_generator, 0))
# send the already filtered carrier to the otherside of the carrier
# the resulting signal from this multiplier is the carrier
# with correct phase but at -38000 Hz.
self.connect(self.stereo_carrier_pll_recovery,
(self.stereo_carrier_generator, 1))
# send the new carrier to one side of the mixer (multiplier)
self.connect(self.stereo_carrier_generator,
(self.stereo_basebander, 0))
# send the demphasized audio to the DSBSC pick off filter, the complex
# DSBSC signal at +38000 Hz is sent to the other side of the mixer/multiplier
# the result is BASEBANDED DSBSC with phase zero!
self.connect(self.fm_demod, self.stereo_dsbsc_filter,
(self.stereo_basebander, 1))
# Pick off the real part since the imaginary is
# theoretically zero and then to one side of a summer
self.connect(self.stereo_basebander, self.LmR_real,
(self.Make_Left, 0))
#take the same real part of the DSBSC baseband signal and
#send it to negative side of a subtracter
self.connect(self.LmR_real, (self.Make_Right, 1))
# Make rds carrier by taking the squared pilot tone and
# multiplying by pilot tone
self.connect(self.stereo_basebander,
(self.rds_carrier_generator, 0))
self.connect(self.stereo_carrier_pll_recovery,
(self.rds_carrier_generator, 1))
# take signal, filter off rds, send into mixer 0 channel
self.connect(self.fm_demod, self.rds_signal_filter,
(self.rds_signal_generator, 0))
# take rds_carrier_generator output and send into mixer 1
# channel
self.connect(self.rds_carrier_generator,
(self.rds_signal_generator, 1))
# send basebanded rds signal and send into "processor"
# which for now is a null sink
self.connect(self.rds_signal_generator, self_rds_signal_processor)
if 1:
# pick off the audio, L+R that is what we used to have and
# send it to the summer
self.connect(self.fm_demod, self.audio_filter, (self.Make_Left, 1))
# take the picked off L+R audio and send it to the PLUS
# side of the subtractor
self.connect(self.audio_filter, (self.Make_Right, 0))
# The result of Make_Left gets (L+R) + (L-R) and results in 2*L
# The result of Make_Right gets (L+R) - (L-R) and results in 2*R
self.connect(self.Make_Left, self.deemph_Left, (self, 0))
self.connect(self.Make_Right, self.deemph_Right, (self, 1))
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
sensitivity=_def_sensitivity,
gain_mu=_def_gain_mu,
mu=_def_mu,
omega_relative_limit=_def_omega_relative_limit,
freq_error=_def_freq_error,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for Gaussian Minimum Shift Key (GFSK)
demodulation.
The input is the complex modulated signal at baseband.
The output is a stream of bits packed 1 bit per byte (the LSB)
Args:
samples_per_symbol: samples per baud (integer)
verbose: Print information about modulator? (bool)
log: Print modualtion data to files? (bool)
Clock recovery parameters. These all have reasonable defaults.
Args:
gain_mu: controls rate of mu adjustment (float)
mu: fractional delay [0.0, 1.0] (float)
omega_relative_limit: sets max variation in omega (float, typically 0.000200 (200 ppm))
freq_error: bit rate error as a fraction
float:
"""
gr.hier_block2.__init__(
self,
"gfsk_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_char)) # Output signature
self._samples_per_symbol = samples_per_symbol
self._gain_mu = gain_mu
self._mu = mu
self._omega_relative_limit = omega_relative_limit
self._freq_error = freq_error
self._differential = False
if samples_per_symbol < 2:
raise TypeError("samples_per_symbol >= 2, is %f" %
samples_per_symbol)
self._omega = samples_per_symbol * (1 + self._freq_error)
if not self._gain_mu:
self._gain_mu = 0.175
self._gain_omega = .25 * self._gain_mu * self._gain_mu # critically damped
# Demodulate FM
#sensitivity = (pi / 2) / samples_per_symbol
self.fmdemod = analog.quadrature_demod_cf(1.0 / sensitivity)
# the clock recovery block tracks the symbol clock and resamples as needed.
# the output of the block is a stream of soft symbols (float)
self.clock_recovery = digital.clock_recovery_mm_ff(
self._omega, self._gain_omega, self._mu, self._gain_mu,
self._omega_relative_limit)
# slice the floats at 0, outputting 1 bit (the LSB of the output byte) per sample
self.slicer = digital.binary_slicer_fb()
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Connect & Initialize base class
self.connect(self, self.fmdemod, self.clock_recovery, self.slicer,
self)
def __init__(self,
dest=_def_dest,
do_imbe=_def_do_imbe,
num_ambe=_def_num_ambe,
wireshark_host=_def_wireshark_host,
udp_port=_def_udp_port,
do_msgq=False,
msgq=None,
audio_output=_def_audio_output,
debug=_def_debug):
"""
Hierarchical block for P25 decoding.
@param debug: debug level
@type debug: int
"""
gr.hier_block2.__init__(
self,
"p25_demod_c",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
assert 0 <= num_ambe <= _def_max_tdma_timeslots
assert not (num_ambe > 1 and dest != 'wav')
self.debug = debug
self.dest = dest
do_output = 1
do_audio_output = True
if msgq is None:
msgq = gr.msg_queue(1)
self.p25_decoders = []
self.audio_s2f = []
self.scaler = []
self.audio_sink = []
self.xorhash = []
num_decoders = 1
if num_ambe > 1:
num_decoders += num_ambe - 1
for slot in xrange(num_decoders):
self.p25_decoders.append(
op25_repeater.p25_frame_assembler(wireshark_host, udp_port,
debug, do_imbe, do_output,
do_msgq, msgq,
do_audio_output, True))
self.p25_decoders[slot].set_slotid(slot)
self.audio_s2f.append(
blocks.short_to_float()) # another ridiculous conversion
self.scaler.append(blocks.multiply_const_ff(1 / 32768.0))
self.xorhash.append('')
if dest == 'wav':
filename = 'default-%f-%d.wav' % (time.time(), slot)
n_channels = 1
sample_rate = 8000
bits_per_sample = 16
self.audio_sink.append(
blocks.wavfile_sink(filename, n_channels, sample_rate,
bits_per_sample))
elif dest == 'audio':
self.audio_sink.append(
audio.sink(_def_audio_rate, audio_output, True))
self.connect(self, self.p25_decoders[slot], self.audio_s2f[slot],
self.scaler[slot], self.audio_sink[slot])
def __init__(
self,
parent,
baseband_freq=0,
ref_scale=2.0,
y_per_div=10,
y_divs=8,
ref_level=50,
sample_rate=1,
pspectrum_len=512,
specest_rate=specest_window.DEFAULT_FRAME_RATE,
average=False,
avg_alpha=None,
title='',
size=specest_window.DEFAULT_WIN_SIZE,
peak_hold=False,
use_persistence=False,
persist_alpha=None,
n=1,
m=150,
nsamples=256,
estimator='esprit',
**kwargs #do not end with a comma
):
#ensure avg alpha
if avg_alpha is None: avg_alpha = 2.0 / specest_rate
#ensure analog alpha
if persist_alpha is None:
actual_specest_rate = float(sample_rate / pspectrum_len) / float(
max(1, int(float(
(sample_rate / pspectrum_len) / specest_rate))))
#print "requested_specest_rate ",specest_rate
#print "actual_specest_rate ",actual_specest_rate
analog_cutoff_freq = 0.5 # Hertz
#calculate alpha from wanted cutoff freq
persist_alpha = 1.0 - math.exp(
-2.0 * math.pi * analog_cutoff_freq / actual_specest_rate)
#init
gr.hier_block2.__init__(
self,
"spectrum_sink",
gr.io_signature(1, 1, self._item_size),
gr.io_signature(0, 0, 0),
)
#blocks
fft = self._specest_chain(sample_rate=sample_rate,
pspectrum_len=pspectrum_len,
frame_rate=specest_rate,
ref_scale=ref_scale,
avg_alpha=avg_alpha,
average=average,
n=n,
m=m,
nsamples=nsamples,
estimator=estimator)
msgq = gr.msg_queue(2)
sink = blocks.message_sink(gr.sizeof_float * pspectrum_len, msgq, True)
#controller
self.controller = pubsub()
self.controller.subscribe(AVERAGE_KEY, fft.set_average)
self.controller.publish(AVERAGE_KEY, fft.average)
self.controller.subscribe(AVG_ALPHA_KEY, fft.set_avg_alpha)
self.controller.publish(AVG_ALPHA_KEY, fft.avg_alpha)
self.controller.subscribe(SAMPLE_RATE_KEY, fft.set_sample_rate)
self.controller.publish(SAMPLE_RATE_KEY, fft.sample_rate)
#start input watcher
common.input_watcher(msgq, self.controller, MSG_KEY)
#create window
self.win = specest_window.specest_window(
parent=parent,
controller=self.controller,
size=size,
title=title,
real=self._real,
spectrum_len=pspectrum_len,
baseband_freq=baseband_freq,
sample_rate_key=SAMPLE_RATE_KEY,
y_per_div=y_per_div,
y_divs=y_divs,
ref_level=ref_level,
average_key=AVERAGE_KEY,
avg_alpha_key=AVG_ALPHA_KEY,
peak_hold=peak_hold,
msg_key=MSG_KEY,
use_persistence=use_persistence,
persist_alpha=persist_alpha,
)
common.register_access_methods(self, self.win)
setattr(self.win, 'set_baseband_freq',
getattr(self, 'set_baseband_freq')) #BACKWARDS
setattr(self.win, 'set_peak_hold',
getattr(self, 'set_peak_hold')) #BACKWARDS
#connect
self.wxgui_connect(self, fft, sink)
def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
sensitivity=_def_sensitivity,
bt=_def_bt,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for Gaussian Frequency Shift Key (GFSK)
modulation.
The input is a byte stream (unsigned char) and the
output is the complex modulated signal at baseband.
Args:
samples_per_symbol: samples per baud >= 2 (integer)
bt: Gaussian filter bandwidth * symbol time (float)
verbose: Print information about modulator? (bool)
debug: Print modualtion data to files? (bool)
"""
gr.hier_block2.__init__(
self,
"gfsk_mod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
samples_per_symbol = int(samples_per_symbol)
self._samples_per_symbol = samples_per_symbol
self._bt = bt
self._differential = False
if not isinstance(samples_per_symbol, int) or samples_per_symbol < 2:
raise TypeError(
"samples_per_symbol must be an integer >= 2, is %r" %
(samples_per_symbol, ))
ntaps = 4 * samples_per_symbol # up to 3 bits in filter at once
#sensitivity = (pi / 2) / samples_per_symbol # phase change per bit = pi / 2
# Turn it into NRZ data.
#self.nrz = digital.bytes_to_syms()
self.unpack = blocks.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST)
self.nrz = digital.chunks_to_symbols_bf([-1, 1])
# Form Gaussian filter
# Generate Gaussian response (Needs to be convolved with window below).
self.gaussian_taps = filter.firdes.gaussian(
1.0, # gain
samples_per_symbol, # symbol_rate
bt, # bandwidth * symbol time
ntaps # number of taps
)
self.sqwave = (1, ) * samples_per_symbol # rectangular window
self.taps = numpy.convolve(numpy.array(self.gaussian_taps),
numpy.array(self.sqwave))
self.gaussian_filter = filter.interp_fir_filter_fff(
samples_per_symbol, self.taps)
# FM modulation
self.fmmod = analog.frequency_modulator_fc(sensitivity)
# small amount of output attenuation to prevent clipping USRP sink
self.amp = blocks.multiply_const_cc(0.999)
if verbose:
self._print_verbage()
if log:
self._setup_logging()
# Connect & Initialize base class
self.connect(self, self.unpack, self.nrz, self.gaussian_filter,
self.fmmod, self.amp, self)
def __init__(self, *args, **kwds):
gr.hier_block2.__init__(self, "horizons", gr.io_signature(0, 0, 0),
gr.io_signature(0, 0, 0))
self.thread = h.horizons_thread(*args, auto_start=False, **kwds)
def __init__(self,
phase_noise_mag=0,
magbal=0,
phasebal=0,
q_ofs=0,
i_ofs=0,
freq_offset=0,
gamma=0,
beta=0):
gr.hier_block2.__init__(
self,
"Radio Impairments Model",
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
gr.io_signature(1, 1, gr.sizeof_gr_complex * 1),
)
##################################################
# Parameters
##################################################
self.phase_noise_mag = phase_noise_mag
self.magbal = magbal
self.phasebal = phasebal
self.q_ofs = q_ofs
self.i_ofs = i_ofs
self.freq_offset = freq_offset
self.gamma = gamma
self.beta = beta
##################################################
# Blocks
##################################################
self.phase_noise = phase_noise_gen(10.0**(phase_noise_mag / 20.0), .01)
self.iq_imbalance = iqbal_gen(magbal, phasebal)
self.channels_distortion_3_gen_0 = distortion_3_gen(beta)
self.channels_distortion_2_gen_0 = distortion_2_gen(gamma)
self.freq_modulator = blocks.multiply_cc()
self.freq_offset_gen = analog.sig_source_c(1.0, analog.GR_COS_WAVE,
freq_offset, 1, 0)
self.freq_modulator_dcoffs = blocks.multiply_cc()
self.freq_offset_conj = blocks.conjugate_cc()
self.dc_offset = blocks.add_const_vcc((i_ofs + q_ofs * 1j, ))
##################################################
# Frequency offset
self.connect((self, 0), (self.freq_modulator, 1))
self.connect((self.freq_offset_gen, 0), (self.freq_offset_conj, 0))
self.connect((self.freq_offset_conj, 0), (self.freq_modulator, 0))
# Most distortions can be strung in a row
self.connect(
(self.freq_modulator, 0),
(self.phase_noise, 0),
(self.channels_distortion_3_gen_0, 0),
(self.channels_distortion_2_gen_0, 0),
(self.iq_imbalance, 0),
(self.dc_offset, 0),
)
# Frequency offset again
self.connect((self.freq_offset_gen, 0),
(self.freq_modulator_dcoffs, 0))
self.connect((self.dc_offset, 0), (self.freq_modulator_dcoffs, 1))
self.connect((self.freq_modulator_dcoffs, 0), (self, 0))
def __init__(self):
gr.hier_block2.__init__(self,
type(self).__name__,
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(0, 0, 0))
self.connect(self, blocks.null_sink(gr.sizeof_gr_complex))
def __init__(
self, top_level_dir, channels=None, start=None, end=None,
repeat=False, throttle=False,
):
"""Initialize source to directory containing Digital RF channels.
Parameters
----------
top_level_dir : string
Either a single top level directory containing Digital RF channel
directories, or a list of such. A directory can be a file system
path or a url, where the url points to a top level directory. Each
must be a local path, or start with 'http://'', 'file://'', or
'ftp://''.
Other Parameters
----------------
channels : None | string | int | iterable of previous
If None, use all available channels in alphabetical order.
Otherwise, use the channels in the order specified in the given
iterable (a string or int is taken as a single-element iterable).
A string is used to specify the channel name, while an int is used
to specify the channel index in the sorted list of available
channel names.
start : None | string | long | iterable of previous
Can be a single value or an iterable of values corresponding to
`channels` giving the start of the channel's playback.
If None or '', the start of the channel's available data is used.
If an integer, it is interpreted as a sample index given in the
number of samples since the epoch (time_since_epoch*sample_rate).
If a float, it is interpreted as a timestamp (seconds since epoch).
If a string, three forms are permitted:
1) a string which can be evaluated to an integer/float and
interpreted as above,
2) a string beginning with '+' and followed by an integer
(float) expression, interpreted as samples (seconds) from
the start of the data, and
3) a time in ISO8601 format, e.g. '2016-01-01T16:24:00Z'
end : None | string | long | iterable of previous
Can be a single value or an iterable of values corresponding to
`channels` giving the end of the channel's playback.
If None or '', the end of the channel's available data is used.
See `start` for a description of how this value is interpreted.
repeat : bool
If True, loop the data continuously from the start after the end
is reached. If False, stop after the data is read once.
throttle : bool
If True, playback the samples at their recorded sample rate. If
False, read samples as quickly as possible.
Notes
-----
A top level directory must contain files in the format:
<channel>/<YYYY-MM-DDTHH-MM-SS/rf@<seconds>.<%03i milliseconds>.h5
If more than one top level directory contains the same channel_name
subdirectory, this is considered the same channel. An error is raised
if their sample rates differ, or if their time periods overlap.
"""
Reader = DigitalRFReader(top_level_dir)
available_channel_names = Reader.get_channels()
self._channel_names = self._get_channel_names(
channels, available_channel_names,
)
if start is None:
start = [None]*len(self._channel_names)
try:
s_iter = iter(start)
except TypeError:
s_iter = iter([start])
if end is None:
end = [None]*len(self._channel_names)
try:
e_iter = iter(end)
except TypeError:
e_iter = iter([end])
# make sources for each channel
self._channels = []
for ch, s, e in zip(self._channel_names, s_iter, e_iter):
chsrc = digital_rf_channel_source(
os.path.join(top_level_dir, ch), start=s, end=e, repeat=repeat,
)
self._channels.append(chsrc)
out_sig_dtypes = [src.out_sig()[0] for src in self._channels]
out_sig = gr.io_signaturev(
len(out_sig_dtypes), len(out_sig_dtypes),
[s.itemsize for s in out_sig_dtypes],
)
in_sig = gr.io_signature(0, 0, 0)
gr.hier_block2.__init__(
self,
name="digital_rf_source",
input_signature=in_sig,
output_signature=out_sig,
)
msg_port_name = pmt.intern('metadata')
self.message_port_register_hier_out('metadata')
for k, src in enumerate(self._channels):
if throttle:
throt = gnuradio.blocks.throttle(
src.out_sig()[0].itemsize, src._sample_rate,
ignore_tags=True,
)
self.connect(src, throt, (self, k))
else:
self.connect(src, (self, k))
self.msg_connect(src, msg_port_name, self, msg_port_name)
