def __init__(self, sample_rate, symbol_rate):
gr.hier_block2.__init__(
self,
"dvb_s_modulator_bc",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
samples_per_symbol = sample_rate / symbol_rate
if samples_per_symbol < 2:
raise TypeError, "Samples per symbol must be >= 2"
# Form symbols with 2 bits per symbol
self.pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST)
self.reunpack = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST)
self.mapper = gr.chunks_to_symbols_bc(mod_constellation)
# Design FIR filter taps for square root raised cosine filter
ntaps = 11 * int(samples_per_symbol * nfilts)
rrc_taps = gr.firdes.root_raised_cosine(nfilts, nfilts, 1.0,
dvb_swig.RRC_ROLLOFF_FACTOR,
ntaps)
# Baseband pulse shaping filter
self.rrc_filter = gr.pfb_arb_resampler_ccf(samples_per_symbol,
rrc_taps)
self.connect(self, self.pack, self.reunpack, self.mapper,
self.rrc_filter, self)
def __init__(self, rate, taps=None, flt_size=32, atten=100):
gr.hier_block2.__init__(self, "pfb_arb_resampler_ccf",
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:
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 = gr.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 = gr.pfb_arb_resampler_ccf(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 test01 (self):
# Test BPSK sync
excess_bw = 0.35
sps = 4
loop_bw = cmath.pi/100.0
nfilts = 32
init_phase = nfilts/2
max_rate_deviation = 1.5
osps = 1
ntaps = 11 * int(sps*nfilts)
#taps = gr.firdes.root_raised_cosine(nfilts, nfilts*sps,
# 1.0, excess_bw, ntaps)
taps = pfb_clock_sync_taps.taps
self.test = digital.pfb_clock_sync_ccf(sps, loop_bw, taps,
nfilts, init_phase,
max_rate_deviation,
osps)
data = 1000*[complex(1,0), complex(-1,0)]
self.src = gr.vector_source_c(data, False)
# pulse shaping interpolation filter
#rrc_taps = gr.firdes.root_raised_cosine(
# nfilts, # gain
# nfilts, # sampling rate based on 32 filters in resampler
# 1.0, # symbol rate
# excess_bw, # excess bandwidth (roll-off factor)
# ntaps)
rrc_taps = pfb_clock_sync_taps.rrc_taps
self.rrc_filter = gr.pfb_arb_resampler_ccf(sps, rrc_taps)
self.snk = gr.vector_sink_c()
self.tb.connect(self.src, self.rrc_filter, self.test, self.snk)
self.tb.run()
expected_result = 1000*[complex(-1,0), complex(1,0)]
dst_data = self.snk.data()
# Only compare last Ncmp samples
Ncmp = 100
len_e = len(expected_result)
len_d = len(dst_data)
expected_result = expected_result[len_e - Ncmp:]
dst_data = dst_data[len_d - Ncmp:]
#for e,d in zip(expected_result, dst_data):
# print e, d
self.assertComplexTuplesAlmostEqual (expected_result, dst_data, 1)
def test01(self):
# Test BPSK sync
excess_bw = 0.35
sps = 4
loop_bw = cmath.pi / 100.0
nfilts = 32
init_phase = nfilts / 2
max_rate_deviation = 1.5
osps = 1
ntaps = 11 * int(sps * nfilts)
#taps = gr.firdes.root_raised_cosine(nfilts, nfilts*sps,
# 1.0, excess_bw, ntaps)
taps = pfb_clock_sync_taps.taps
self.test = digital.pfb_clock_sync_ccf(sps, loop_bw, taps, nfilts,
init_phase, max_rate_deviation,
osps)
data = 1000 * [complex(1, 0), complex(-1, 0)]
self.src = gr.vector_source_c(data, False)
# pulse shaping interpolation filter
#rrc_taps = gr.firdes.root_raised_cosine(
# nfilts, # gain
# nfilts, # sampling rate based on 32 filters in resampler
# 1.0, # symbol rate
# excess_bw, # excess bandwidth (roll-off factor)
# ntaps)
rrc_taps = pfb_clock_sync_taps.rrc_taps
self.rrc_filter = gr.pfb_arb_resampler_ccf(sps, rrc_taps)
self.snk = gr.vector_sink_c()
self.tb.connect(self.src, self.rrc_filter, self.test, self.snk)
self.tb.run()
expected_result = 1000 * [complex(-1, 0), complex(1, 0)]
dst_data = self.snk.data()
# Only compare last Ncmp samples
Ncmp = 100
len_e = len(expected_result)
len_d = len(dst_data)
expected_result = expected_result[len_e - Ncmp:]
dst_data = dst_data[len_d - Ncmp:]
#for e,d in zip(expected_result, dst_data):
# print e, d
self.assertComplexTuplesAlmostEqual(expected_result, dst_data, 1)
def __init__(self, rate, taps, flt_size=32):
gr.hier_block2.__init__(self, "pfb_arb_resampler_ccf",
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._taps = taps
self._size = flt_size
self.pfb = gr.pfb_arb_resampler_ccf(self._rate, self._taps, self._size)
self.connect(self, self.pfb)
self.connect(self.pfb, self)
def __init__(self, sample_rate, symbol_rate): gr.hier_block2.__init__(self, "dvb_s_modulator_bc", gr.io_signature(1, 1, gr.sizeof_char), # Input signature gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature samples_per_symbol = sample_rate / symbol_rate if samples_per_symbol < 2: raise TypeError, "Samples per symbol must be >= 2" # Form symbols with 2 bits per symbol self.pack = gr.unpacked_to_packed_bb(1, gr.GR_MSB_FIRST) self.reunpack = gr.packed_to_unpacked_bb(2, gr.GR_MSB_FIRST) self.mapper = gr.chunks_to_symbols_bc(mod_constellation) # Design FIR filter taps for square root raised cosine filter ntaps = 11 * int(samples_per_symbol * nfilts) rrc_taps = gr.firdes.root_raised_cosine(nfilts, nfilts, 1.0, dvb_swig.RRC_ROLLOFF_FACTOR, ntaps) # Baseband pulse shaping filter self.rrc_filter = gr.pfb_arb_resampler_ccf(samples_per_symbol, rrc_taps) self.connect(self, self.pack, self.reunpack, self.mapper, self.rrc_filter, self)
def __init__(self, constellation,
samples_per_symbol=_def_samples_per_symbol,
differential=_def_differential,
excess_bw=_def_excess_bw,
gray_coded=True,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for RRC-filtered differential generic modulation.
The input is a byte stream (unsigned char) and the
output is the complex modulated signal at baseband.
@param constellation: determines the modulation type
@type constellation: gnuradio.digital.gr_constellation
@param samples_per_symbol: samples per baud >= 2
@type samples_per_symbol: float
@param excess_bw: Root-raised cosine filter excess bandwidth
@type excess_bw: float
@param gray_coded: turn gray coding on/off
@type gray_coded: bool
@param verbose: Print information about modulator?
@type verbose: bool
@param log: Log modulation data to files?
@type log: bool
"""
gr.hier_block2.__init__(self, "generic_mod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._constellation = constellation.base()
self._samples_per_symbol = samples_per_symbol
self._excess_bw = excess_bw
self._differential = differential
if self._samples_per_symbol < 2:
raise TypeError, ("sbp must be >= 2, is %f" % self._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 gray_coded == True:
self.symbol_mapper = gr.map_bb(self._constellation.pre_diff_code())
if differential:
self.diffenc = gr.diff_encoder_bb(arity)
self.chunks2symbols = gr.chunks_to_symbols_bc(self._constellation.points())
# pulse shaping filter
nfilts = 32
ntaps = nfilts * 11 * int(self._samples_per_symbol) # make nfilts filters of ntaps each
self.rrc_taps = gr.firdes.root_raised_cosine(
nfilts, # gain
nfilts, # sampling rate based on 32 filters in resampler
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = gr.pfb_arb_resampler_ccf(self._samples_per_symbol,
self.rrc_taps)
# Connect
blocks = [self, self.bytes2chunks]
if gray_coded == True:
blocks.append(self.symbol_mapper)
if differential:
blocks.append(self.diffenc)
blocks += [self.chunks2symbols, self.rrc_filter, self]
self.connect(*blocks)
if verbose:
self._print_verbage()
if log:
self._setup_logging()
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,
"dqpsk2_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 samples_per_symbol < 2:
raise TypeError, ("sbp must be >= 2, is %f" % 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(psk.binary_to_gray[arity])
else:
self.symbol_mapper = gr.map_bb(psk.binary_to_ungray[arity])
self.diffenc = gr.diff_encoder_bb(arity)
rot = .707 + .707j
rotated_const = map(lambda pt: pt * rot, psk.constellation[arity])
self.chunks2symbols = gr.chunks_to_symbols_bc(rotated_const)
# pulse shaping filter
nfilts = 32
ntaps = 11 * int(
nfilts *
self._samples_per_symbol) # make nfilts filters of ntaps each
self.rrc_taps = gr.firdes.root_raised_cosine(
nfilts, # gain
nfilts, # sampling rate based on 32 filters in resampler
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = gr.pfb_arb_resampler_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,
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 differential BPSK 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 baud >= 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 log: Log modulation data to files?
@type log: bool
"""
gr.hier_block2.__init__(self, "dbpsk_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 self._samples_per_symbol < 2:
raise TypeError, ("sbp must be an integer >= 2, is %d" % self._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(psk.binary_to_gray[arity])
else:
self.symbol_mapper = gr.map_bb(psk.binary_to_ungray[arity])
self.diffenc = gr.diff_encoder_bb(arity)
self.chunks2symbols = gr.chunks_to_symbols_bc(psk.constellation[arity])
# pulse shaping filter
nfilts = 32
ntaps = nfilts * 11 * int(self._samples_per_symbol) # make nfilts filters of ntaps each
self.rrc_taps = gr.firdes.root_raised_cosine(
nfilts, # gain
nfilts, # sampling rate based on 32 filters in resampler
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = gr.pfb_arb_resampler_ccf(self._samples_per_symbol, self.rrc_taps)
# Connect
self.connect(self, self.bytes2chunks, self.symbol_mapper, self.diffenc,
self.chunks2symbols, self.rrc_filter, self)
if verbose:
self._print_verbage()
if log:
self._setup_logging()
def __init__(self,
constellation,
samples_per_symbol=_def_samples_per_symbol,
differential=_def_differential,
excess_bw=_def_excess_bw,
gray_coded=True,
verbose=_def_verbose,
log=_def_log):
"""
Hierarchical block for RRC-filtered differential generic modulation.
The input is a byte stream (unsigned char) and the
output is the complex modulated signal at baseband.
@param constellation: determines the modulation type
@type constellation: gnuradio.digital.gr_constellation
@param samples_per_symbol: samples per baud >= 2
@type samples_per_symbol: float
@param excess_bw: Root-raised cosine filter excess bandwidth
@type excess_bw: float
@param gray_coded: turn gray coding on/off
@type gray_coded: bool
@param verbose: Print information about modulator?
@type verbose: bool
@param log: Log modulation data to files?
@type log: bool
"""
gr.hier_block2.__init__(
self,
"generic_mod",
gr.io_signature(1, 1, gr.sizeof_char), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
self._constellation = constellation.base()
self._samples_per_symbol = samples_per_symbol
self._excess_bw = excess_bw
self._differential = differential
if self._samples_per_symbol < 2:
raise TypeError, ("sbp must be >= 2, is %f" %
self._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 gray_coded == True:
self.symbol_mapper = digital.map_bb(
self._constellation.pre_diff_code())
if differential:
self.diffenc = digital.diff_encoder_bb(arity)
self.chunks2symbols = digital.chunks_to_symbols_bc(
self._constellation.points())
# pulse shaping filter
nfilts = 32
ntaps = nfilts * 11 * int(
self._samples_per_symbol) # make nfilts filters of ntaps each
self.rrc_taps = gr.firdes.root_raised_cosine(
nfilts, # gain
nfilts, # sampling rate based on 32 filters in resampler
1.0, # symbol rate
self._excess_bw, # excess bandwidth (roll-off factor)
ntaps)
self.rrc_filter = gr.pfb_arb_resampler_ccf(self._samples_per_symbol,
self.rrc_taps)
# Connect
blocks = [self, self.bytes2chunks]
if gray_coded == True:
blocks.append(self.symbol_mapper)
if differential:
blocks.append(self.diffenc)
blocks += [self.chunks2symbols, self.rrc_filter, self]
self.connect(*blocks)
if verbose:
self._print_verbage()
if log:
self._setup_logging()
def __init__(self, options, input_filename):
gr.top_block.__init__(self)
gr.enable_realtime_scheduling()
if options.real:
sizeof_input_samples = gr.sizeof_float
else:
sizeof_input_samples = gr.sizeof_gr_complex
self.src = gr.file_source(sizeof_input_samples,
input_filename,
repeat = options.loop)
self.u = generic_usrp_sink_c(interface = options.interface,
mac_addr = options.mac_addr,
subdev_spec = options.tx_subdev_spec)
print 'Using %s' % str(self.u)
print 'Possible tx frequency range: %s - %s' % \
(n2s(self.u.freq_range()[0]), n2s(self.u.freq_range()[1]))
# we need to find the closest decimation rate the USRP can handle
# to the input file's sampling rate
try:
ideal_interp = self.u.dac_rate() / options.rate
# pick the closest interpolation rate
interp = [x for x in self.u.get_interp_rates()
if x <= ideal_interp][-1]
self.u.set_interp(interp)
except IndexError:
sys.stderr.write('Failed to set USRP interpolation rate\n')
raise SystemExit, 1
output_rate = self.u.dac_rate() / interp
resamp_ratio = output_rate / options.rate
# since the input file sample rate may not be exactly what our
# output rate of the USRP (as determined by the interpolation rate),
# we need to resample our input to the output rate
num_filters = 32
cutoff = 0.99 * options.rate / 2.
transition = 0.1 * options.rate / 2.
resamp_taps = gr.firdes_low_pass(num_filters * 1.0,
num_filters * options.rate,
cutoff,
transition)
self.resamp = gr.pfb_arb_resampler_ccf(resamp_ratio,
resamp_taps,
num_filters)
if options.gain is None:
# if no gain was specified, use the mid-point in dB
g = self.u.gain_range()
options.gain = float(g[0]+g[1])/2
self.u.set_gain(options.gain)
res = self.u.set_center_freq(options.freq)
if not res:
sys.stderr.write('Failed to set frequency\n')
raise SystemExit, 1
if options.real:
# our samples are real
# we need to convert them to complex without a hilbert filter
self.hilbert = gr.hilbert_fc(64)
self.connect(self.src, self.hilbert, self.resamp, self.u)
else:
# our samples are complex
self.connect(self.src, self.resamp, self.u)