def __init__(self,
samples_per_symbol=_def_samples_per_symbol,
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):
gr.hier_block2.__init__(
self,
"gmsk_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,
samples_per_symbol=_def_samples_per_symbol,
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):
gr.hier_block2.__init__(self, "gmsk_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 test_binary_slicer_fb(self):
expected_result = ( 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1)
src_data = (-1, 1, -1, -1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, 1)
src_data = [s + (1 - random.random()) for s in src_data] # add some noise
src = gr.vector_source_f(src_data)
op = digital.binary_slicer_fb()
dst = gr.vector_sink_b()
self.tb.connect(src, op)
self.tb.connect(op, dst)
self.tb.run() # run the graph and wait for it to finish
actual_result = dst.data() # fetch the contents of the sink
#print "actual result", actual_result
#print "expected result", expected_result
self.assertFloatTuplesAlmostEqual(expected_result, actual_result)
def test_binary_slicer_fb (self):
expected_result = ( 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1)
src_data = (-1, 1, -1, -1, 1, 1, -1, -1, -1, 1, 1, 1, -1, 1, 1, 1, 1)
src_data = [s + (1 - random.random()) for s in src_data] # add some noise
src = gr.vector_source_f (src_data)
op = digital_swig.binary_slicer_fb ()
dst = gr.vector_sink_b ()
self.tb.connect (src, op)
self.tb.connect (op, dst)
self.tb.run () # run the graph and wait for it to finish
actual_result = dst.data () # fetch the contents of the sink
#print "actual result", actual_result
#print "expected result", expected_result
self.assertFloatTuplesAlmostEqual (expected_result, actual_result)
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)
@param samples_per_symbol: samples per baud
@type samples_per_symbol: integer
@param verbose: Print information about modulator?
@type verbose: bool
@param log: Print modualtion data to files?
@type log: bool
Clock recovery parameters. These all have reasonble defaults.
@param gain_mu: controls rate of mu adjustment
@type gain_mu: float
@param mu: fractional delay [0.0, 1.0]
@type mu: float
@param omega_relative_limit: sets max variation in omega
@type omega_relative_limit: float, typically 0.000200 (200 ppm)
@param freq_error: bit rate error as a fraction
@param 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 = gr.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)