def __init__(self, sample_rate, noise_voltage, frequency_offset, seed=False):
gr.hier_block2.__init__(self, "awgn_channel",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
# Create the Gaussian noise source
if not seed:
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_voltage)
else:
rseed = int(time.time())
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_voltage, rseed)
self.adder = gr.add_cc()
# Create the frequency offset
self.offset = gr.sig_source_c(1, gr.GR_SIN_WAVE,
frequency_offset, 1.0, 0.0)
self.mixer = gr.multiply_cc()
# Connect the components
self.connect(self, (self.mixer, 0))
self.connect(self.offset, (self.mixer, 1))
self.connect(self.mixer, (self.adder, 0))
self.connect(self.noise, (self.adder, 1))
self.connect(self.adder, self)
def __init__(self, Np=32, P=128, L=2,
filename=None, sample_type='complex', verbose=True):
gr.top_block.__init__(self)
if filename is None:
src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
if verbose:
print "Using Gaussian noise source."
else:
if sample_type == 'complex':
src = gr.file_source(gr.sizeof_gr_complex, filename, True)
else:
fsrc = gr.file_source(gr.sizeof_float, filename, True)
src = gr.float_to_complex()
self.connect(fsrc, src)
if verbose:
print "Reading data from %s" % filename
if verbose:
print "FAM configuration:"
print "N' = %d" % Np
print "P = %d" % P
print "L = %d" % L
#print "Δf = %f" % asfd
sink = gr.null_sink(gr.sizeof_float * 2 * Np)
self.cyclo_fam = specest.cyclo_fam(Np, P, L)
self.connect(src, self.cyclo_fam, sink)
def __init__(self, rx_callback, SNR):
"""
@param options Optparse option field for command line arguments.
@param rx_callback Callback function for the event when a packet is received.
"""
gr.flow_graph.__init__(self)
self.samples_per_symbol = 2
self.data_rate = 2000000
payload_size = 128 # bytes
self.packet_transmitter = ieee802_15_4_pkt.ieee802_15_4_mod_pkts(
self, spb=self.samples_per_symbol, msgq_limit=2)
# add some noise
print " Setting SNR to ", SNR
add = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, pow(10.0, -SNR / 20.0))
self.packet_receiver = ieee802_15_4_pkt.ieee802_15_4_demod_pkts(
self,
callback=rx_callback,
sps=self.samples_per_symbol,
symbol_rate=self.data_rate,
threshold=-1)
self.connect(self.packet_transmitter, (add, 0))
self.connect(noise, (add, 1))
self.connect(add, self.packet_receiver)
def __init__(self, N, fs, bw0, bw1, tw, atten, D):
gr.top_block.__init__(self)
self._nsamps = N
self._fs = fs
self._bw0 = bw0
self._bw1 = bw1
self._tw = tw
self._at = atten
self._decim = D
taps = filter.firdes.complex_band_pass_2(1, self._fs,
self._bw0, self._bw1,
self._tw, self._at)
print "Num. Taps: ", len(taps)
self.src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
self.head = gr.head(gr.sizeof_gr_complex, self._nsamps)
self.filt0 = filter.fft_filter_ccc(self._decim, taps)
self.vsnk_src = gr.vector_sink_c()
self.vsnk_out = gr.vector_sink_c()
self.connect(self.src, self.head, self.vsnk_src)
self.connect(self.head, self.filt0, self.vsnk_out)
def __init__(self, frame, panel, vbox, argv):
stdgui2.std_top_block.__init__ (self, frame, panel, vbox, argv)
pspectrum_len = 1024
# build our flow graph
input_rate = 2e6
#Generate some noise
noise = gr.noise_source_c(gr.GR_GAUSSIAN, 1.0/10)
# Generate a complex sinusoid
#source = gr.file_source(gr.sizeof_gr_complex, 'foobar2.dat', repeat=True)
src1 = gr.sig_source_c (input_rate, gr.GR_SIN_WAVE, -500e3, 1)
src2 = gr.sig_source_c (input_rate, gr.GR_SIN_WAVE, 500e3, 1)
src3 = gr.sig_source_c (input_rate, gr.GR_SIN_WAVE, -250e3, 2)
# We add these throttle blocks so that this demo doesn't
# suck down all the CPU available. Normally you wouldn't use these.
thr1 = gr.throttle(gr.sizeof_gr_complex, input_rate)
sink1 = spectrum_sink_c (panel, title="Spectrum Sink", pspectrum_len=pspectrum_len,
sample_rate=input_rate, baseband_freq=0,
ref_level=0, y_per_div=20, y_divs=10, m = 70, n = 3, nsamples = 1024)
vbox.Add (sink1.win, 1, wx.EXPAND)
combine1=gr.add_cc()
self.connect(src1,(combine1,0))
self.connect(src2,(combine1,1))
self.connect(src3,(combine1,2))
self.connect(noise, (combine1,3))
self.connect(combine1,thr1, sink1)
def __init__(self, noise_voltage=0.0, frequency_offset=0.0, epsilon=1.0, taps=[1.0,0.0], noise_seed=3021):
''' Creates a channel model that includes:
- AWGN noise power in terms of noise voltage
- A frequency offest in the channel in ratio
- A timing offset ratio to model clock difference (epsilon)
- Multipath taps
'''
gr.hier_block2.__init__(self, "channel_model",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature
#print epsilon
self.timing_offset = gr.fractional_interpolator_cc(0, epsilon)
self.multipath = gr.fir_filter_ccc(1, taps)
self.noise_adder = gr.add_cc()
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_voltage, noise_seed)
self.freq_offset = gr.sig_source_c(1, gr.GR_SIN_WAVE, frequency_offset, 1.0, 0.0)
self.mixer_offset = gr.multiply_cc()
self.connect(self, self.timing_offset, self.multipath)
self.connect(self.multipath, (self.mixer_offset,0))
self.connect(self.freq_offset,(self.mixer_offset,1))
self.connect(self.mixer_offset, (self.noise_adder,1))
self.connect(self.noise, (self.noise_adder,0))
self.connect(self.noise_adder, self)
def test_001_detect(self):
""" Send two bursts, with zeros in between, and check
they are both detected at the correct position and no
false alarms occur """
n_zeros = 15
fft_len = 32
cp_len = 4
sig_len = (fft_len + cp_len) * 10
sync_symbol = [(random.randint(0, 1) * 2) - 1
for x in range(fft_len / 2)] * 2
tx_signal = [0,] * n_zeros + \
sync_symbol[-cp_len:] + \
sync_symbol + \
[(random.randint(0, 1)*2)-1 for x in range(sig_len)]
tx_signal = tx_signal * 2
add = gr.add_cc()
sync = digital.ofdm_sync_sc_cfb(fft_len, cp_len)
sink_freq = gr.vector_sink_f()
sink_detect = gr.vector_sink_b()
self.tb.connect(gr.vector_source_c(tx_signal), (add, 0))
self.tb.connect(gr.noise_source_c(gr.GR_GAUSSIAN, .005), (add, 1))
self.tb.connect(add, sync)
self.tb.connect((sync, 0), sink_freq)
self.tb.connect((sync, 1), sink_detect)
self.tb.run()
sig1_detect = sink_detect.data()[0:len(tx_signal) / 2]
sig2_detect = sink_detect.data()[len(tx_signal) / 2:]
self.assertTrue(
abs(sig1_detect.index(1) - (n_zeros + fft_len + cp_len)) < cp_len)
self.assertTrue(
abs(sig2_detect.index(1) - (n_zeros + fft_len + cp_len)) < cp_len)
self.assertEqual(numpy.sum(sig1_detect), 1)
self.assertEqual(numpy.sum(sig2_detect), 1)
def __init__(self, rx_callback, spb, alpha, SNR):
# m is constellation size
# if diff==True we are doing DxPSK
gr.flow_graph.__init__(self)
fg = self
# transmitter
self.packet_transmitter = bbn_80211b_mod_pkts(fg, spb=spb, alpha=alpha,
gain=1)
# add some noise
add = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, pow(10.0,-SNR/20.0))
# channel filter
rx_filt_taps = gr.firdes.low_pass(1,spb,0.8,0.1,gr.firdes.WIN_HANN)
rx_filt = gr.fir_filter_ccf(1,rx_filt_taps)
# receiver
self.bit_receiver = bbn_80211b_demod_pkts(self, spb=spb, alpha=alpha,
callback=rx_callback)
fg.connect(self.packet_transmitter, (add,0))
fg.connect(noise, (add,1))
#xfile=gr.file_sink(gr.sizeof_gr_complex,"txdata");
#fg.connect(add, xfile)
fg.connect(add, rx_filt)
fg.connect(rx_filt, self.bit_receiver)
def test_002_freq (self):
""" Add a fine frequency offset and see if that get's detected properly """
fft_len = 32
cp_len = 4
freq_offset = 0.1 # Must stay < 2*pi/fft_len = 0.196 (otherwise, it's coarse)
sig_len = (fft_len + cp_len) * 10
sync_symbol = [(random.randint(0, 1)*2)-1 for x in range(fft_len/2)] * 2
tx_signal = sync_symbol[-cp_len:] + \
sync_symbol + \
[(random.randint(0, 1)*2)-1 for x in range(sig_len)]
mult = gr.multiply_cc()
add = gr.add_cc()
sync = digital.ofdm_sync_sc_cfb(fft_len, cp_len)
sink_freq = gr.vector_sink_f()
sink_detect = gr.vector_sink_b()
self.tb.connect(gr.vector_source_c(tx_signal), (mult, 0), (add, 0))
self.tb.connect(gr.sig_source_c(2 * numpy.pi, gr.GR_SIN_WAVE, freq_offset, 1.0), (mult, 1))
self.tb.connect(gr.noise_source_c(gr.GR_GAUSSIAN, .01), (add, 1))
self.tb.connect(add, sync)
self.tb.connect((sync, 0), sink_freq)
self.tb.connect((sync, 1), sink_detect)
self.tb.run()
phi_hat = sink_freq.data()[sink_detect.data().index(1)]
est_freq_offset = 2 * phi_hat / fft_len
self.assertAlmostEqual(est_freq_offset, freq_offset, places=2)
def run_flow_graph(sync_sym1, sync_sym2, data_sym):
top_block = gr.top_block()
carr_offset = random.randint(-max_offset/2, max_offset/2) * 2
tx_data = shift_tuple(sync_sym1, carr_offset) + \
shift_tuple(sync_sym2, carr_offset) + \
shift_tuple(data_sym, carr_offset)
channel = [rand_range(min_chan_ampl, max_chan_ampl) * numpy.exp(1j * rand_range(0, 2 * numpy.pi)) for x in range(fft_len)]
src = gr.vector_source_c(tx_data, False, fft_len)
chan= gr.multiply_const_vcc(channel)
noise = gr.noise_source_c(gr.GR_GAUSSIAN, wgn_amplitude)
add = gr.add_cc(fft_len)
chanest = digital.ofdm_chanest_vcvc(sync_sym1, sync_sym2, 1)
sink = gr.vector_sink_c(fft_len)
top_block.connect(src, chan, (add, 0), chanest, sink)
top_block.connect(noise, gr.stream_to_vector(gr.sizeof_gr_complex, fft_len), (add, 1))
top_block.run()
channel_est = None
carr_offset_hat = 0
rx_sym_est = [0,] * fft_len
tags = sink.tags()
for tag in tags:
if pmt.pmt_symbol_to_string(tag.key) == 'ofdm_sync_carr_offset':
carr_offset_hat = pmt.pmt_to_long(tag.value)
self.assertEqual(carr_offset, carr_offset_hat)
if pmt.pmt_symbol_to_string(tag.key) == 'ofdm_sync_chan_taps':
channel_est = shift_tuple(pmt.pmt_c32vector_elements(tag.value), carr_offset)
shifted_carrier_mask = shift_tuple(carrier_mask, carr_offset)
for i in range(fft_len):
if shifted_carrier_mask[i] and channel_est[i]:
self.assertAlmostEqual(channel[i], channel_est[i], places=0)
rx_sym_est[i] = (sink.data()[i] / channel_est[i]).real
return (carr_offset, list(shift_tuple(rx_sym_est, -carr_offset_hat)))
def test_001_detect (self):
""" Send two bursts, with zeros in between, and check
they are both detected at the correct position and no
false alarms occur """
n_zeros = 15
fft_len = 32
cp_len = 4
sig_len = (fft_len + cp_len) * 10
sync_symbol = [(random.randint(0, 1)*2)-1 for x in range(fft_len/2)] * 2
tx_signal = [0,] * n_zeros + \
sync_symbol[-cp_len:] + \
sync_symbol + \
[(random.randint(0, 1)*2)-1 for x in range(sig_len)]
tx_signal = tx_signal * 2
add = gr.add_cc()
sync = digital.ofdm_sync_sc_cfb(fft_len, cp_len)
sink_freq = gr.vector_sink_f()
sink_detect = gr.vector_sink_b()
self.tb.connect(gr.vector_source_c(tx_signal), (add, 0))
self.tb.connect(gr.noise_source_c(gr.GR_GAUSSIAN, .01), (add, 1))
self.tb.connect(add, sync)
self.tb.connect((sync, 0), sink_freq)
self.tb.connect((sync, 1), sink_detect)
self.tb.run()
sig1_detect = sink_detect.data()[0:len(tx_signal)/2]
sig2_detect = sink_detect.data()[len(tx_signal)/2:]
self.assertTrue(abs(sig1_detect.index(1) - (n_zeros + fft_len + cp_len)) < cp_len)
self.assertTrue(abs(sig2_detect.index(1) - (n_zeros + fft_len + cp_len)) < cp_len)
self.assertEqual(numpy.sum(sig1_detect), 1)
self.assertEqual(numpy.sum(sig2_detect), 1)
def __init__(self, dBm, pfa, pfd, nTrials):
gr.top_block.__init__(self)
# Constants
samp_rate = 2.4e6
fft_size = 4096
samples_per_band = 16
tcme = 1.9528
output_pfa = True
debug_stats = False
histogram = False
primary_user_location = 0
useless_bw = 200000.0
src_data = [0+0j]*fft_size*nTrials
voltage = self.powerToAmplitude(dBm);
# Blocks
src = gr.vector_source_c(src_data)
noise = gr.noise_source_c(gr.GR_GAUSSIAN, voltage, 42)
add = gr.add_vcc()
s2v = gr.stream_to_vector(gr.sizeof_gr_complex, fft_size)
fftb = fft.fft_vcc(fft_size, True, (window.blackmanharris(1024)), False, 1)
ss = howto.spectrum_sensing_cf(samp_rate,fft_size,samples_per_band,pfd,pfa,tcme,output_pfa,debug_stats,primary_user_location,useless_bw,histogram)
self.sink = gr.vector_sink_f()
# Connections
self.connect(src, add, s2v, fftb, ss, self.sink)
self.connect(noise, (add, 1))
def setUp (self):
print "qa_remove_cp2_cvc SetUp!"
self.fftl = fftl = 2048
cpl = 144*fftl/2048
cpl0 = 160*fftl/2048
self.slotl = slotl = 7*fftl+6*cpl+cpl0
self.tb = gr.top_block ()
#provide test data
self.src = gr.noise_source_c(gr.GR_GAUSSIAN,1)
self.head = gr.head( gr.sizeof_gr_complex, 10*slotl )
self.tag = lte.pss_tagging_cc(fftl)
# set up tagging block
self.tag.set_half_frame_start(0)
self.tag.set_N_id_2(1)
self.tag.lock()
# UUT
self.rcp = lte.remove_cp2_cvc(fftl)
# sinks
self.snk = gr.vector_sink_c(fftl)
self.tagsnc = gr.tag_debug(gr.sizeof_gr_complex*fftl, "remove_cp2_cvc")
# connect blocks
self.tb.connect(self.src, self.head, self.tag, self.rcp, self.snk )
def set_waveform(self, type):
self.lock()
self.disconnect_all()
if type == gr.GR_SIN_WAVE or type == gr.GR_CONST_WAVE:
self._src = gr.sig_source_c(
self[SAMP_RATE_KEY], # Sample rate
type, # Waveform type
self[WAVEFORM_FREQ_KEY], # Waveform frequency
self[AMPLITUDE_KEY], # Waveform amplitude
self[WAVEFORM_OFFSET_KEY]) # Waveform offset
elif type == gr.GR_GAUSSIAN or type == gr.GR_UNIFORM:
self._src = gr.noise_source_c(type, self[AMPLITUDE_KEY])
elif type == "2tone":
self._src1 = gr.sig_source_c(self[SAMP_RATE_KEY], gr.GR_SIN_WAVE,
self[WAVEFORM_FREQ_KEY],
self[AMPLITUDE_KEY] / 2.0, 0)
if (self[WAVEFORM2_FREQ_KEY] is None):
self[WAVEFORM2_FREQ_KEY] = -self[WAVEFORM_FREQ_KEY]
self._src2 = gr.sig_source_c(self[SAMP_RATE_KEY], gr.GR_SIN_WAVE,
self[WAVEFORM2_FREQ_KEY],
self[AMPLITUDE_KEY] / 2.0, 0)
self._src = gr.add_cc()
self.connect(self._src1, (self._src, 0))
self.connect(self._src2, (self._src, 1))
elif type == "sweep":
# rf freq is center frequency
# waveform_freq is total swept width
# waveform2_freq is sweep rate
# will sweep from (rf_freq-waveform_freq/2) to (rf_freq+waveform_freq/2)
if self[WAVEFORM2_FREQ_KEY] is None:
self[WAVEFORM2_FREQ_KEY] = 0.1
self._src1 = gr.sig_source_f(self[SAMP_RATE_KEY], gr.GR_TRI_WAVE,
self[WAVEFORM2_FREQ_KEY], 1.0, -0.5)
self._src2 = gr.frequency_modulator_fc(
self[WAVEFORM_FREQ_KEY] * 2 * math.pi / self[SAMP_RATE_KEY])
self._src = gr.multiply_const_cc(self[AMPLITUDE_KEY])
self.connect(self._src1, self._src2, self._src)
else:
raise RuntimeError("Unknown waveform type")
self.connect(self._src, self._u)
self.unlock()
if self._verbose:
print "Set baseband modulation to:", waveforms[type]
if type == gr.GR_SIN_WAVE:
print "Modulation frequency: %sHz" % (n2s(
self[WAVEFORM_FREQ_KEY]), )
print "Initial phase:", self[WAVEFORM_OFFSET_KEY]
elif type == "2tone":
print "Tone 1: %sHz" % (n2s(self[WAVEFORM_FREQ_KEY]), )
print "Tone 2: %sHz" % (n2s(self[WAVEFORM2_FREQ_KEY]), )
elif type == "sweep":
print "Sweeping across %sHz to %sHz" % (n2s(
-self[WAVEFORM_FREQ_KEY] /
2.0), n2s(self[WAVEFORM_FREQ_KEY] / 2.0))
print "Sweep rate: %sHz" % (n2s(self[WAVEFORM2_FREQ_KEY]), )
print "TX amplitude:", self[AMPLITUDE_KEY]
def __init__(self, noise_ampl=0):
"""
Parameters:
noise_ampl: float
"""
gr.hier_block2.__init__(
self, "Additive White Gaussian Noise Generator",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex),
)
##################################################
# Parameters
##################################################
self.noise_ampl = noise_ampl
##################################################
# Blocks
##################################################
self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN,
noise_ampl, 42)
self.gr_add_xx_0 = gr.add_vcc(1)
##################################################
# Connections
##################################################
self.connect((self, 0), (self.gr_add_xx_0, 0))
self.connect((self.gr_noise_source_x_0, 0), (self.gr_add_xx_0, 1))
self.connect((self.gr_add_xx_0, 0), (self, 0))
def __init__(self, fg, noise_voltage=0.0, frequency_offset=0.0, epsilon=1.0, taps=[1.0,0.0]):
''' Creates a channel model that includes:
- AWGN noise power in terms of noise voltage
- A frequency offest in the channel in ratio
- A timing offset ratio to model clock difference (epsilon)
- Multipath taps
'''
print epsilon
self.timing_offset = gr.fractional_interpolator_cc(0, epsilon)
self.multipath = gr.fir_filter_ccc(1, taps)
self.noise_adder = gr.add_cc()
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN,noise_voltage)
self.freq_offset = gr.sig_source_c(1, gr.GR_SIN_WAVE, frequency_offset, 1.0, 0.0)
self.mixer_offset = gr.multiply_cc()
fg.connect(self.timing_offset, self.multipath)
fg.connect(self.multipath, (self.mixer_offset,0))
fg.connect(self.freq_offset,(self.mixer_offset,1))
fg.connect(self.mixer_offset, (self.noise_adder,1))
fg.connect(self.noise, (self.noise_adder,0))
gr.hier_block.__init__(self, fg, self.timing_offset, self.noise_adder)
def __init__(self, n_sinusoids = 1, SNR = 10, samp_rate = 32e3, nsamples = 2048):
gr.hier_block2.__init__(self, "ESPRIT/MUSIC signal generator",
gr.io_signature(0, 0, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
sigampl = 10.0**(SNR/10.0) # noise power is 1
self.srcs = list()
self.n_sinusoids = n_sinusoids
self.samp_rate = samp_rate
# create our signals ...
for s in range(n_sinusoids):
self.srcs.append(gr.sig_source_c(samp_rate,
gr.GR_SIN_WAVE,1000 * s + 2000,
numpy.sqrt(sigampl/n_sinusoids)))
seed = ord(os.urandom(1))
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, 1, seed)
self.add = gr.add_cc()
self.head = gr.head(gr.sizeof_gr_complex, nsamples)
self.sink = gr.vector_sink_f(vlen=n_sinusoids)
# wire it up ...
for s in range(n_sinusoids):
self.connect(self.srcs[s], (self.add, s))
# Additive noise
self.connect(self.noise, (self.add, n_sinusoids))
self.connect(self.add, self.head, self)
def __init__(self):
gr.top_block.__init__(self, "FFT Sink Test")
fft_size = 256
# build our flow graph
input_rate = 2048.0e3
#Generate some noise
noise = gr.noise_source_c(gr.GR_UNIFORM, 1.0/10)
# Generate a complex sinusoid
src1 = gr.sig_source_c (input_rate, gr.GR_SIN_WAVE, 2e3, 1)
#src1 = gr.sig_source_c(input_rate, gr.GR_CONST_WAVE, 57.50e3, 1)
# We add these throttle blocks so that this demo doesn't
# suck down all the CPU available. Normally you wouldn't use these.
thr1 = gr.throttle(gr.sizeof_gr_complex, input_rate)
test_fft = zmq_fft_sink_c(title="Complex Data", fft_size=fft_size,
sample_rate=input_rate, baseband_freq=100e3,
ref_level=0, y_per_div=20, y_divs=10)
combine1 = gr.add_cc()
#self.connect(src1, (combine1, 0))
#self.connect(noise,(combine1, 1))
self.connect(src1, thr1, test_fft)
def __init__(self, rx_callback, SNR):
"""
@param options Optparse option field for command line arguments.
@param rx_callback Callback function for the event when a packet is received.
"""
gr.flow_graph.__init__(self)
self.samples_per_symbol = 2
self.data_rate = 2000000
payload_size = 128 # bytes
self.packet_transmitter = ieee802_15_4_pkt.ieee802_15_4_mod_pkts(self, spb=self.samples_per_symbol, msgq_limit=2)
# add some noise
print " Setting SNR to ", SNR
add = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, pow(10.0,-SNR/20.0))
self.packet_receiver = ieee802_15_4_pkt.ieee802_15_4_demod_pkts(self,
callback=rx_callback,
sps=self.samples_per_symbol,
symbol_rate=self.data_rate,
threshold=-1)
self.connect (self.packet_transmitter, (add,0))
self.connect (noise, (add,1))
self.connect(add, self.packet_receiver)
def test_003_multiburst (self):
""" Send several bursts, see if the number of detects is correct.
Burst lengths and content are random.
"""
n_bursts = 42
fft_len = 32
cp_len = 4
tx_signal = []
for i in xrange(n_bursts):
sync_symbol = [(random.randint(0, 1)*2)-1 for x in range(fft_len/2)] * 2
tx_signal += [0,] * random.randint(0, 2*fft_len) + \
sync_symbol[-cp_len:] + \
sync_symbol + \
[(random.randint(0, 1)*2)-1 for x in range(fft_len * random.randint(5,23))]
add = gr.add_cc()
sync = digital.ofdm_sync_sc_cfb(fft_len, cp_len)
sink_freq = gr.vector_sink_f()
sink_detect = gr.vector_sink_b()
self.tb.connect(gr.vector_source_c(tx_signal), (add, 0))
self.tb.connect(gr.noise_source_c(gr.GR_GAUSSIAN, .005), (add, 1))
self.tb.connect(add, sync)
self.tb.connect((sync, 0), sink_freq)
self.tb.connect((sync, 1), sink_detect)
self.tb.run()
self.assertEqual(numpy.sum(sink_detect.data()), n_bursts,
msg="""Because of statistics, it is possible (though unlikely)
that the number of detected bursts differs slightly. If the number of detects is
off by one or two, run the test again and see what happen.
Detection error was: %d """ % (numpy.sum(sink_detect.data()) - n_bursts)
)
def build_graph (input, raw, snr, freq_offset, coeffs, mag):
# Initialize empty flow graph
fg = gr.top_block ()
# Set up file source
src = gr.file_source (1, input)
# Set up GMSK modulator, 2 samples per symbol
mod = gmsk_mod(2)
# Amplify the signal
tx_amp = 1
amp = gr.multiply_const_cc(1)
amp.set_k(tx_amp)
# Compute proper noise voltage based on SNR
SNR = 10.0**(snr/10.0)
power_in_signal = abs(tx_amp)**2
noise_power = power_in_signal/SNR
noise_voltage = math.sqrt(noise_power)
# Generate noise
rseed = int(time.time())
noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_voltage, rseed)
adder = gr.add_cc()
fg.connect(noise, (adder, 1))
# Create the frequency offset, 0 for now
offset = gr.sig_source_c(1, gr.GR_SIN_WAVE, freq_offset, 1.0, 0.0)
mixer = gr.multiply_cc()
fg.connect(offset, (mixer, 1))
# Pass the noisy data to the matched filter
dfile = open(coeffs, 'r')
data = []
for line in dfile:
data.append(complex(*map(float,line.strip().strip("()").split(" "))).conjugate())
dfile.close()
data.reverse()
mfilter = gr.fir_filter_ccc(1, data)
# Connect the flow graph
fg.connect(src, mod)
fg.connect(mod, (mixer, 0))
fg.connect(mixer, (adder, 0))
if mag:
raw_dst = gr.file_sink (gr.sizeof_float, raw)
magnitude = gr.complex_to_mag(1)
fg.connect(adder, mfilter, magnitude, raw_dst)
else:
raw_dst = gr.file_sink (gr.sizeof_gr_complex, raw)
fg.connect(adder, mfilter, raw_dst)
print "SNR(db): " + str(snr)
print "Frequency Offset: " + str(freq_offset)
return fg
def __init__(self, frame, panel, vbox, argv):
stdgui2.std_top_block.__init__(self, frame, panel, vbox, argv)
fft_size = 256
# build our flow graph
input_rate = 2048.0e3
# Generate some noise
noise = gr.noise_source_c(gr.GR_UNIFORM, 1.0 / 10)
# Generate a complex sinusoid
# src1 = gr.sig_source_c (input_rate, gr.GR_SIN_WAVE, 2e3, 1)
src1 = gr.sig_source_c(input_rate, gr.GR_CONST_WAVE, 57.50e3, 1)
# We add these throttle blocks so that this demo doesn't
# suck down all the CPU available. Normally you wouldn't use these.
thr1 = gr.throttle(gr.sizeof_gr_complex, input_rate)
sink1 = fft_sink_c(
panel,
title="Complex Data",
fft_size=fft_size,
sample_rate=input_rate,
baseband_freq=100e3,
ref_level=0,
y_per_div=20,
y_divs=10,
)
vbox.Add(sink1.win, 1, wx.EXPAND)
combine1 = gr.add_cc()
self.connect(src1, (combine1, 0))
self.connect(noise, (combine1, 1))
self.connect(combine1, thr1, sink1)
# src2 = gr.sig_source_f (input_rate, gr.GR_SIN_WAVE, 2e3, 1)
src2 = gr.sig_source_f(input_rate, gr.GR_CONST_WAVE, 57.50e3, 1)
thr2 = gr.throttle(gr.sizeof_float, input_rate)
sink2 = fft_sink_f(
panel,
title="Real Data",
fft_size=fft_size * 2,
sample_rate=input_rate,
baseband_freq=100e3,
ref_level=0,
y_per_div=20,
y_divs=10,
)
vbox.Add(sink2.win, 1, wx.EXPAND)
combine2 = gr.add_ff()
c2f2 = gr.complex_to_float()
self.connect(src2, (combine2, 0))
self.connect(noise, c2f2, (combine2, 1))
self.connect(combine2, thr2, sink2)
def _instantiate_blocks (self):
self.src = None
self.u = usrp.sink_c (0, self.interp)
self.siggen = gr.sig_source_c (self.usb_freq (),
gr.GR_SIN_WAVE,
self.waveform_freq,
self.waveform_ampl,
self.waveform_offset)
self.noisegen = gr.noise_source_c (gr.GR_UNIFORM,
self.waveform_ampl)
def __init__(self, frame, panel, vbox, argv):
stdgui2.std_top_block.__init__(self, frame, panel, vbox, argv)
fft_size = 256
# build our flow graph
input_rate = 2048.0e3
#Generate some noise
noise = gr.noise_source_c(gr.GR_UNIFORM, 1.0 / 10)
# Generate a complex sinusoid
#src1 = gr.sig_source_c (input_rate, gr.GR_SIN_WAVE, 2e3, 1)
src1 = gr.sig_source_c(input_rate, gr.GR_CONST_WAVE, 57.50e3, 1)
# We add these throttle blocks so that this demo doesn't
# suck down all the CPU available. Normally you wouldn't use these.
thr1 = gr.throttle(gr.sizeof_gr_complex, input_rate)
sink1 = fft_sink_c(panel,
title="Complex Data",
fft_size=fft_size,
sample_rate=input_rate,
baseband_freq=100e3,
ref_level=0,
y_per_div=20,
y_divs=10)
vbox.Add(sink1.win, 1, wx.EXPAND)
combine1 = gr.add_cc()
self.connect(src1, (combine1, 0))
self.connect(noise, (combine1, 1))
self.connect(combine1, thr1, sink1)
#src2 = gr.sig_source_f (input_rate, gr.GR_SIN_WAVE, 2e3, 1)
src2 = gr.sig_source_f(input_rate, gr.GR_CONST_WAVE, 57.50e3, 1)
thr2 = gr.throttle(gr.sizeof_float, input_rate)
sink2 = fft_sink_f(panel,
title="Real Data",
fft_size=fft_size * 2,
sample_rate=input_rate,
baseband_freq=100e3,
ref_level=0,
y_per_div=20,
y_divs=10)
vbox.Add(sink2.win, 1, wx.EXPAND)
combine2 = gr.add_ff()
c2f2 = gr.complex_to_float()
self.connect(src2, (combine2, 0))
self.connect(noise, c2f2, (combine2, 1))
self.connect(combine2, thr2, sink2)
def _instantiate_blocks (self):
self.src = None
self.u = usrp.sink_c (0, self.interp,fpga_filename=gpio.fpga_filename)
self.siggen = gr.sig_source_c (self.usb_freq (),
gr.GR_SIN_WAVE,
self.waveform_freq,
self.waveform_ampl,
self.waveform_offset)
self.noisegen = gr.noise_source_c (gr.GR_UNIFORM,
self.waveform_ampl)
self.vecgen = gr.vector_source_c ([complex(1.0,0.0),complex(0.0,0.0),complex(1.0,1.0),complex(0.0,1.0)],True)
def _instantiate_blocks(self):
self.src = None
self.u = usrp.sink_c(0, self.interp)
self.siggen = gr.sig_source_c(
self.usb_freq(), gr.GR_SIN_WAVE, self.waveform_freq, self.waveform_ampl, self.waveform_offset
)
self.noisegen = gr.noise_source_c(gr.GR_UNIFORM, self.waveform_ampl)
self.head = None
if self.nsamples > 0:
self.head = gr.head(gr.sizeof_gr_complex, int(self.nsamples))
def test_002 (self):
""" Stream some data through the block to see it all works. """
Np = 128
P = 512
L = 4
src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
head = gr.head(gr.sizeof_gr_complex, P * L)
cyclo_fam = specest.cyclo_fam (Np,P,L)
dst = gr.vector_sink_f(2*Np)
self.tb.connect(src, head, cyclo_fam, dst)
try:
self.tb.run()
except:
self.fail("Something's wrong -- an exception was thrown during runtime.")
def test_depuncture_viterbi_cb(self): """ Performs some very basic tests of the depuncture-viterbi block """ # 1. Random data expected_result = () src = gr.noise_source_c(gr.GR_GAUSSIAN, ampl=math.sqrt(1/2), seed=0) head = gr.head(gr.sizeof_gr_complex, 100000) depuncture_viterbi = dvb_swig.depuncture_viterbi_cb([1,1]) dst = gr.vector_sink_b() self.tb.connect(src, head, depuncture_viterbi, dst) self.tb.run() self.assertEqual(expected_result, dst.data());
def test_002(self):
""" Stream some data through the block to see it all works. """
Np = 128
P = 512
L = 4
src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
head = gr.head(gr.sizeof_gr_complex, P * L)
cyclo_fam = specest.cyclo_fam(Np, P, L)
dst = gr.vector_sink_f(2 * Np)
self.tb.connect(src, head, cyclo_fam, dst)
try:
self.tb.run()
except:
self.fail(
"Something's wrong -- an exception was thrown during runtime.")
def __init__(self, noise_dB=-20., fir_taps=[1]):
gr.hier_block2.__init__(self, 'my_channel',
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_gr_complex))
noise_adder = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, 10**(noise_dB/20.), random.randint(0,2**30))
# normalize taps
firtabsum = float(sum(map(abs,fir_taps)))
fir_taps = [ i / firtabsum for i in fir_taps]
multipath = gr.fir_filter_ccc(1,fir_taps)
self.connect(noise, (noise_adder,1))
self.connect(self, noise_adder, multipath, self)
self.__dict__.update(locals()) # didn't feel like using self all over the place
def test_002_stream(self):
""" Stream some data through the block to see it all works. """
block_len = 256
fft_len = 128
order = 6
n_blocks = 100
src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
head = gr.head(gr.sizeof_gr_complex, n_blocks * block_len)
burg = specest.burg(block_len, fft_len, order)
dst = gr.vector_sink_f(fft_len)
self.tb.connect(src, head, burg, dst)
try:
self.tb.run()
except:
self.fail("Something's wrong -- an exception was thrown during runtime.")
def test_002_stream (self):
""" Monkey test """
block_len = 256
fft_len = 128
order = 6
n_blocks = 100
src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
head = gr.head(gr.sizeof_gr_complex, n_blocks * block_len)
fmcov = specest.fmcov(block_len, fft_len, order)
dst = gr.vector_sink_f(fft_len)
self.tb.connect(src, head, fmcov, dst)
try:
self.tb.run()
except:
self.fail("Something's wrong -- an exception was thrown during runtime.")
def __init__(self, noise_dB=-20., fir_taps=[1]):
gr.hier_block2.__init__(self, 'my_channel',
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
noise_adder = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, 10**(noise_dB / 20.),
random.randint(0, 2**30))
# normalize taps
firtabsum = float(sum(map(abs, fir_taps)))
fir_taps = [i / firtabsum for i in fir_taps]
multipath = gr.fir_filter_ccc(1, fir_taps)
self.connect(noise, (noise_adder, 1))
self.connect(self, noise_adder, multipath, self)
self.__dict__.update(
locals()) # didn't feel like using self all over the place
def __init__(self, EbN0):
gr.top_block.__init__(self)
self.const = digital.qpsk_constellation()
# Source is N_BITS bits, non-repeated
data = map(int, numpy.random.randint(0, self.const.arity(), N_BITS/self.const.bits_per_symbol()))
src = gr.vector_source_b(data, False)
mod = gr.chunks_to_symbols_bc((self.const.points()), 1)
add = gr.add_vcc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN,
self.EbN0_to_noise_voltage(EbN0),
RAND_SEED)
demod = digital.constellation_decoder_cb(self.const.base())
ber = BitErrors(self.const.bits_per_symbol())
self.sink = gr.vector_sink_f()
self.connect(src, mod, add, demod, ber, self.sink)
self.connect(noise, (add, 1))
self.connect(src, (ber, 1))
def __init__(self, constellation, f, N0=0.25, seed=-666L):
"""
constellation - a constellation object used for modulation.
f - a finite state machine specification used for coding.
N0 - noise level
seed - random seed
"""
super(trellis_tb, self).__init__()
# packet size in bits (make it multiple of 16 so it can be packed in a short)
packet_size = 1024 * 16
# bits per FSM input symbol
bitspersymbol = int(round(math.log(f.I()) /
math.log(2))) # bits per FSM input symbol
# packet size in trellis steps
K = packet_size / bitspersymbol
# TX
src = gr.lfsr_32k_source_s()
# packet size in shorts
src_head = gr.head(gr.sizeof_short, packet_size / 16)
# unpack shorts to symbols compatible with the FSM input cardinality
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol, gr.GR_MSB_FIRST)
# initial FSM state = 0
enc = trellis.encoder_ss(f, 0)
mod = gr.chunks_to_symbols_sc(constellation.points(), 1)
# CHANNEL
add = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
# data preprocessing to generate metrics for Viterbi
metrics = trellis.constellation_metrics_cf(
constellation.base(), digital_swig.TRELLIS_EUCLIDEAN)
# Put -1 if the Initial/Final states are not set.
va = trellis.viterbi_s(f, K, 0, -1)
# pack FSM input symbols to shorts
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol, gr.GR_MSB_FIRST)
# check the output
self.dst = gr.check_lfsr_32k_s()
self.connect(src, src_head, s2fsmi, enc, mod)
self.connect(mod, (add, 0))
self.connect(noise, (add, 1))
self.connect(add, metrics, va, fsmi2s, self.dst)
def run_flow_graph(sync_sym1, sync_sym2, data_sym):
top_block = gr.top_block()
carr_offset = random.randint(-max_offset / 2, max_offset / 2) * 2
tx_data = shift_tuple(sync_sym1, carr_offset) + \
shift_tuple(sync_sym2, carr_offset) + \
shift_tuple(data_sym, carr_offset)
channel = [
rand_range(min_chan_ampl, max_chan_ampl) *
numpy.exp(1j * rand_range(0, 2 * numpy.pi))
for x in range(fft_len)
]
src = gr.vector_source_c(tx_data, False, fft_len)
chan = gr.multiply_const_vcc(channel)
noise = gr.noise_source_c(gr.GR_GAUSSIAN, wgn_amplitude)
add = gr.add_cc(fft_len)
chanest = digital.ofdm_chanest_vcvc(sync_sym1, sync_sym2, 1)
sink = gr.vector_sink_c(fft_len)
top_block.connect(src, chan, (add, 0), chanest, sink)
top_block.connect(
noise, gr.stream_to_vector(gr.sizeof_gr_complex, fft_len),
(add, 1))
top_block.run()
channel_est = None
carr_offset_hat = 0
rx_sym_est = [
0,
] * fft_len
tags = sink.tags()
for tag in tags:
if pmt.pmt_symbol_to_string(
tag.key) == 'ofdm_sync_carr_offset':
carr_offset_hat = pmt.pmt_to_long(tag.value)
self.assertEqual(carr_offset, carr_offset_hat)
if pmt.pmt_symbol_to_string(tag.key) == 'ofdm_sync_chan_taps':
channel_est = shift_tuple(
pmt.pmt_c32vector_elements(tag.value), carr_offset)
shifted_carrier_mask = shift_tuple(carrier_mask, carr_offset)
for i in range(fft_len):
if shifted_carrier_mask[i] and channel_est[i]:
self.assertAlmostEqual(channel[i],
channel_est[i],
places=0)
rx_sym_est[i] = (sink.data()[i] / channel_est[i]).real
return (carr_offset, list(shift_tuple(rx_sym_est,
-carr_offset_hat)))
def test_002_stream(self):
""" Stream some data through the block to see it all works. """
block_len = 256
fft_len = 128
order = 6
n_blocks = 100
src = gr.noise_source_c(gr.GR_GAUSSIAN, 1)
head = gr.head(gr.sizeof_gr_complex, n_blocks * block_len)
fcov = specest.fcov(block_len, fft_len, order)
dst = gr.vector_sink_f(fft_len)
self.tb.connect(src, head, fcov, dst)
try:
self.tb.run()
except:
self.fail(
"Something's wrong -- an exception was thrown during runtime.")
def __init__(self,ampl_i,band,symbol_rate,sps):
gr.hier_block2.__init__(self,"Channel",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_gr_complex))
self.symbol_rate = symbol_rate
self.sample_rate=symbol_rate*sps
self.fading = False
self.adder = gr.add_cc()
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, 1, -42)
self.ampl = gr.multiply_const_cc(ampl_i)
self.taps = gr.firdes.low_pass_2 (1,280,band/2,5,80,gr.firdes.WIN_KAISER)
self.filter=gr.fir_filter_ccf(1,self.taps)
#Connects
self.connect(self,self.filter,(self.adder,0))
self.connect(self.noise, self.ampl, (self.adder,1))
self.connect(self.adder, self)
def __init__(self, constellation, f, N0=0.25, seed=-666L):
"""
constellation - a constellation object used for modulation.
f - a finite state machine specification used for coding.
N0 - noise level
seed - random seed
"""
super(trellis_tb, self).__init__()
# packet size in bits (make it multiple of 16 so it can be packed in a short)
packet_size = 1024*16
# bits per FSM input symbol
bitspersymbol = int(round(math.log(f.I())/math.log(2))) # bits per FSM input symbol
# packet size in trellis steps
K = packet_size/bitspersymbol
# TX
src = gr.lfsr_32k_source_s()
# packet size in shorts
src_head = gr.head (gr.sizeof_short, packet_size/16)
# unpack shorts to symbols compatible with the FSM input cardinality
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol, gr.GR_MSB_FIRST)
# initial FSM state = 0
enc = trellis.encoder_ss(f, 0)
mod = gr.chunks_to_symbols_sc(constellation.points(), 1)
# CHANNEL
add = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
# data preprocessing to generate metrics for Viterbi
metrics = trellis.constellation_metrics_cf(constellation.base(), digital_swig.TRELLIS_EUCLIDEAN)
# Put -1 if the Initial/Final states are not set.
va = trellis.viterbi_s(f, K, 0, -1)
# pack FSM input symbols to shorts
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol, gr.GR_MSB_FIRST)
# check the output
self.dst = gr.check_lfsr_32k_s()
self.connect (src, src_head, s2fsmi, enc, mod)
self.connect (mod, (add, 0))
self.connect (noise, (add, 1))
self.connect (add, metrics, va, fsmi2s, self.dst)
def __init__(self, EbN0):
gr.top_block.__init__(self)
self.const = digital.qpsk_constellation()
# Source is N_BITS bits, non-repeated
data = map(
int,
numpy.random.randint(0, self.const.arity(),
N_BITS / self.const.bits_per_symbol()))
src = gr.vector_source_b(data, False)
mod = gr.chunks_to_symbols_bc((self.const.points()), 1)
add = gr.add_vcc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN,
self.EbN0_to_noise_voltage(EbN0), RAND_SEED)
demod = digital.constellation_decoder_cb(self.const.base())
ber = BitErrors(self.const.bits_per_symbol())
self.sink = gr.vector_sink_f()
self.connect(src, mod, add, demod, ber, self.sink)
self.connect(noise, (add, 1))
self.connect(src, (ber, 1))
def __init__(self, ampl_i, band, symbol_rate, sps):
gr.hier_block2.__init__(self, "Channel",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self.symbol_rate = symbol_rate
self.sample_rate = symbol_rate * sps
self.fading = False
self.adder = gr.add_cc()
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, 1, -42)
self.ampl = gr.multiply_const_cc(ampl_i)
self.taps = gr.firdes.low_pass_2(1, 280, band / 2, 5, 80,
gr.firdes.WIN_KAISER)
self.filter = gr.fir_filter_ccf(1, self.taps)
#Connects
self.connect(self, self.filter, (self.adder, 0))
self.connect(self.noise, self.ampl, (self.adder, 1))
self.connect(self.adder, self)
def __init__(self, frame, panel, vbox, argv):
stdgui2.std_top_block.__init__(self, frame, panel, vbox, argv)
self.frame = frame
self.panel = panel
parser = OptionParser(usage="%prog: [options]")
parser.add_option("-N", "--dpsslength", type="int",
help="Length of the DPSS", default="512")
parser.add_option("-B", "--timebandwidthproduct", type="float",
help="Time Bandwidthproduct used to calculate the DPSS", default="3")
parser.add_option("-K", "--tapers", type="int",
help="Number of Tapers used to calculate the Spectrum", default="5")
parser.add_option("-W", "--weighting", type="choice", choices=("unity", "eigenvalues" ,"adaptive" ),
help="weighting-type to be used (unity, eigenvalues, adaptive) ", default="adaptive")
(options, args) = parser.parse_args ()
self.options = options
#setting up our signal
self.samplingrate = 48000
self.source = gr.sig_source_c(self.samplingrate, gr.GR_SIN_WAVE, 3000, 1)
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN,0.5)
self.add = gr.add_cc()
self.throttle = gr.throttle(gr.sizeof_gr_complex, self.samplingrate)
#the actual spectrum estimator
self.v2s = gr.vector_to_stream(gr.sizeof_float, self.options.dpsslength)
self.mtm = specest.mtm(N = self.options.dpsslength, NW = self.options.timebandwidthproduct, K = self.options.tapers, weighting = self.options.weighting)
self.scope = specest.spec_sink_f(panel,
title='Spectrum with %s weighting, Length %i and %i Tapers' % ( self.options.weighting, self.options.dpsslength, self.options.tapers ),
spec_size=self.options.dpsslength,
sample_rate=self.samplingrate,
ref_level=80,
avg_alpha=0.8,
y_per_div=20)
self.connect(self.source, (self.add, 0) )
self.connect(self.noise, (self.add, 1) )
self.connect(self.add, self.throttle, self.mtm)
self.connect(self.mtm, self.v2s, self.scope)
self._build_gui(vbox)
def __init__(self):
gr.top_block.__init__(self)
# Make a local QtApp so we can start it from our side
self.qapp = QtGui.QApplication(sys.argv)
fftsize = 2048
self.src = gr.sig_source_c(1, gr.GR_SIN_WAVE, 0.1, 1)
self.nse = gr.noise_source_c(gr.GR_GAUSSIAN, 0.0)
self.add = gr.add_cc()
self.thr = gr.throttle(gr.sizeof_gr_complex, 100 * fftsize)
self.snk = qtgui.sink_c(fftsize, gr.firdes.WIN_BLACKMAN_hARRIS)
self.connect(self.src, (self.add, 0))
self.connect(self.nse, (self.add, 1))
self.connect(self.add, self.thr, self.snk)
# Tell the sink we want it displayed
self.pyobj = sip.wrapinstance(self.snk.pyqwidget(), QtGui.QWidget)
self.pyobj.show()
def __init__(self, noise_voltage, frequency_offset):
gr.hier_block2.__init__(self, "awgn_channel",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self.noise_adder = gr.add_cc()
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_voltage)
self.offset = gr.sig_source_c(1, gr.GR_SIN_WAVE, frequency_offset, 1.0,
0.0)
self.mixer_offset = gr.multiply_cc()
self.connect(self, (self.mixer_offset, 0))
self.connect(self.offset, (self.mixer_offset, 1))
self.connect(self.mixer_offset, (self.noise_adder, 1))
self.connect(self.noise, (self.noise_adder, 0))
self.connect(self.noise_adder, self)
try:
gr.hier_block.update_var_names(self, "awgn_channel", vars())
gr.hier_block.update_var_names(self, "awgn_channel", vars(self))
except:
pass
def __init__(self, N, fs, fd, ca_shift, snr=0):
gr.hier_block2.__init__(self, "simulated_source",
gr.io_signature(0, 0, 0),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
code = ca_code(svn=1, fs=fs, ca_shift=ca_shift)
code = ravel(array([code for _ in range(N)]))
n = arange(len(code))
f = e**(2j * pi * fd * n / fs)
x = (code * f)
# Add noise.
signal_power = sum(sqrt(abs(x))) / len(x)
noise_voltage = sqrt(signal_power / 10**(snr / 10.0))
src = gr.vector_source_c(x)
noise = gr.noise_source_c(gr.GR_UNIFORM, noise_voltage)
add = gr.add_cc()
self.connect(src, (add, 0))
self.connect(noise, (add, 1))
self.connect(add, self)
def __init__(self):
grc_wxgui.top_block_gui.__init__(self, title="Top Block")
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 32000
##################################################
# Blocks
##################################################
self.usrp2_sink_xxxx_0 = usrp2.sink_32fc()
self.usrp2_sink_xxxx_0.set_interp(16)
self.usrp2_sink_xxxx_0.set_center_freq(900e6)
self.usrp2_sink_xxxx_0.set_gain(0)
self.usrp2_sink_xxxx_0.config_mimo(usrp2.MC_WE_DONT_LOCK)
self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN, 1, 42)
##################################################
# Connections
##################################################
self.connect((self.gr_noise_source_x_0, 0),
(self.usrp2_sink_xxxx_0, 0))
def __init__(self, noise_voltage, sensitivity):
gr.hier_block2.__init__(self, "variable_awgn_channel",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self.noise_adder = gr.add_cc()
self.noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_voltage)
self.noise_amp = gr.multiply_cc()
self.offset = gr.frequency_modulator_fc(sensitivity)
self.mixer_offset = gr.multiply_cc()
self.connect(self, (self.mixer_offset, 0))
self.connect(self.offset, (self.mixer_offset, 1))
self.connect(self.mixer_offset, (self.noise_adder, 1))
self.connect(self.noise, (self.noise_amp, 0))
self.connect(self.noise_amp, (self.noise_adder, 0))
self.connect(self.noise_adder, self)
try:
gr.hier_block.update_var_names(self, "var_awgn_channel", vars())
gr.hier_block.update_var_names(self, "var_awgn_channel",
vars(self))
except:
pass
def __init__(self,
freq_corr=0,
avg_frames=1,
decim=16,
N_id_2=0,
N_id_1=134):
grc_wxgui.top_block_gui.__init__(self, title="Sss Corr5 Gui")
_icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png"
self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY))
##################################################
# Parameters
##################################################
self.freq_corr = freq_corr
self.avg_frames = avg_frames
self.decim = decim
self.N_id_2 = N_id_2
self.N_id_1 = N_id_1
##################################################
# Variables
##################################################
self.vec_half_frame = vec_half_frame = 30720 * 5 / decim
self.symbol_start = symbol_start = 144 / decim
self.slot_0_10 = slot_0_10 = 1
self.samp_rate = samp_rate = 30720e3 / decim
self.rot = rot = 0
self.noise_level = noise_level = 0
self.fft_size = fft_size = 2048 / decim
self.N_re = N_re = 62
##################################################
# Blocks
##################################################
_rot_sizer = wx.BoxSizer(wx.VERTICAL)
self._rot_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_rot_sizer,
value=self.rot,
callback=self.set_rot,
label='rot',
converter=forms.float_converter(),
proportion=0,
)
self._rot_slider = forms.slider(
parent=self.GetWin(),
sizer=_rot_sizer,
value=self.rot,
callback=self.set_rot,
minimum=0,
maximum=1,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_rot_sizer)
self.notebook_0 = self.notebook_0 = wx.Notebook(self.GetWin(),
style=wx.NB_TOP)
self.notebook_0.AddPage(grc_wxgui.Panel(self.notebook_0), "SSS ML")
self.notebook_0.AddPage(grc_wxgui.Panel(self.notebook_0), "SSS equ")
self.notebook_0.AddPage(grc_wxgui.Panel(self.notebook_0), "SSS in")
self.notebook_0.AddPage(grc_wxgui.Panel(self.notebook_0), "PSS equ")
self.notebook_0.AddPage(grc_wxgui.Panel(self.notebook_0), "PSS ch est")
self.notebook_0.AddPage(grc_wxgui.Panel(self.notebook_0), "foo")
self.Add(self.notebook_0)
_noise_level_sizer = wx.BoxSizer(wx.VERTICAL)
self._noise_level_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_noise_level_sizer,
value=self.noise_level,
callback=self.set_noise_level,
label='noise_level',
converter=forms.float_converter(),
proportion=0,
)
self._noise_level_slider = forms.slider(
parent=self.GetWin(),
sizer=_noise_level_sizer,
value=self.noise_level,
callback=self.set_noise_level,
minimum=0,
maximum=10,
num_steps=100,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_noise_level_sizer)
self.wxgui_scopesink2_0_1_0_1 = scopesink2.scope_sink_c(
self.notebook_0.GetPage(3).GetWin(),
title="Scope Plot",
sample_rate=samp_rate,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=2,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Counts",
)
self.notebook_0.GetPage(3).Add(self.wxgui_scopesink2_0_1_0_1.win)
self.wxgui_scopesink2_0_1_0_0 = scopesink2.scope_sink_c(
self.notebook_0.GetPage(2).GetWin(),
title="Scope Plot",
sample_rate=samp_rate,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=1,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Counts",
)
self.notebook_0.GetPage(2).Add(self.wxgui_scopesink2_0_1_0_0.win)
self.wxgui_scopesink2_0_1_0 = scopesink2.scope_sink_c(
self.notebook_0.GetPage(1).GetWin(),
title="Scope Plot",
sample_rate=samp_rate,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=1,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Counts",
)
self.notebook_0.GetPage(1).Add(self.wxgui_scopesink2_0_1_0.win)
self.wxgui_scopesink2_0_1 = scopesink2.scope_sink_f(
self.notebook_0.GetPage(0).GetWin(),
title="Scope Plot",
sample_rate=100 / avg_frames,
v_scale=0,
v_offset=0,
t_scale=0,
ac_couple=False,
xy_mode=False,
num_inputs=1,
trig_mode=gr.gr_TRIG_MODE_AUTO,
y_axis_label="Counts",
)
self.notebook_0.GetPage(0).Add(self.wxgui_scopesink2_0_1.win)
_symbol_start_sizer = wx.BoxSizer(wx.VERTICAL)
self._symbol_start_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_symbol_start_sizer,
value=self.symbol_start,
callback=self.set_symbol_start,
label='symbol_start',
converter=forms.int_converter(),
proportion=0,
)
self._symbol_start_slider = forms.slider(
parent=self.GetWin(),
sizer=_symbol_start_sizer,
value=self.symbol_start,
callback=self.set_symbol_start,
minimum=0,
maximum=144 / decim,
num_steps=144 / decim,
style=wx.SL_HORIZONTAL,
cast=int,
proportion=1,
)
self.Add(_symbol_start_sizer)
self.sss_ml_fd_0 = sss_ml_fd(
decim=decim,
avg_frames=avg_frames,
N_id_1=N_id_1,
N_id_2=N_id_2,
slot_0_10=slot_0_10,
)
self.pss_chan_est2_0 = pss_chan_est2(N_id_2=N_id_2, )
self.gr_vector_to_stream_0_0_1_0 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, N_re)
self.gr_vector_to_stream_0_0_1 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, N_re)
self.gr_vector_to_stream_0_0_0 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, N_re)
self.gr_vector_to_stream_0_0 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, N_re)
self.gr_vector_to_stream_0 = gr.vector_to_stream(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_vector_source_x_0_0_0 = gr.vector_source_c(
(gen_pss_fd(N_id_2, N_re, False).get_data()), True, N_re)
self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex * 1, samp_rate)
self.gr_stream_to_vector_0_0 = gr.stream_to_vector(
gr.sizeof_gr_complex * 1, N_re)
self.gr_stream_to_vector_0 = gr.stream_to_vector(
gr.sizeof_gr_complex * 1, fft_size)
self.gr_stream_mux_0 = gr.stream_mux(gr.sizeof_gr_complex * 1,
(N_re / 2, N_re / 2))
self.gr_null_source_0 = gr.null_source(gr.sizeof_gr_complex * 1)
self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN,
noise_level, 0)
self.gr_multiply_xx_1_0 = gr.multiply_vcc(N_re)
self.gr_multiply_xx_1 = gr.multiply_vcc(N_re)
self.gr_multiply_const_vxx_0 = gr.multiply_const_vcc(
(0.005 * exp(rot * 2 * numpy.pi * 1j), ))
self.gr_keep_m_in_n_0_0 = gr.keep_m_in_n(gr.sizeof_gr_complex,
N_re / 2, fft_size,
(fft_size - N_re) / 2 - 1)
self.gr_keep_m_in_n_0 = gr.keep_m_in_n(gr.sizeof_gr_complex, N_re / 2,
fft_size, (fft_size) / 2)
self.gr_file_source_0 = gr.file_source(
gr.sizeof_gr_complex * 1,
"/home/user/git/gr-lte/gr-lte/test/octave/foo_sss_td_in.cfile",
True)
self.gr_fft_vxx_0 = gr.fft_vcc(fft_size, True,
(window.blackmanharris(1024)), True, 1)
self.gr_deinterleave_0 = gr.deinterleave(gr.sizeof_gr_complex * N_re)
self.gr_channel_model_0 = gr.channel_model(
noise_voltage=0.005 * noise_level,
frequency_offset=0.0,
epsilon=1,
taps=(0.005 * exp(rot * 2 * numpy.pi * 1j), ),
noise_seed=0,
)
self.gr_add_xx_0 = gr.add_vcc(1)
self.blks2_selector_0_0 = grc_blks2.selector(
item_size=gr.sizeof_gr_complex * 1,
num_inputs=2,
num_outputs=1,
input_index=0,
output_index=0,
)
self.blks2_selector_0 = grc_blks2.selector(
item_size=gr.sizeof_gr_complex * 1,
num_inputs=3,
num_outputs=2,
input_index=0,
output_index=0,
)
##################################################
# Connections
##################################################
self.connect((self.gr_noise_source_x_0, 0), (self.gr_add_xx_0, 1))
self.connect((self.gr_add_xx_0, 0), (self.gr_multiply_const_vxx_0, 0))
self.connect((self.blks2_selector_0, 0), (self.gr_channel_model_0, 0))
self.connect((self.blks2_selector_0, 1), (self.gr_add_xx_0, 0))
self.connect((self.gr_channel_model_0, 0),
(self.blks2_selector_0_0, 0))
self.connect((self.gr_multiply_const_vxx_0, 0),
(self.blks2_selector_0_0, 1))
self.connect((self.gr_file_source_0, 0), (self.blks2_selector_0, 0))
self.connect((self.blks2_selector_0_0, 0), (self.gr_throttle_0, 0))
self.connect((self.gr_deinterleave_0, 0),
(self.gr_vector_to_stream_0_0_0, 0))
self.connect((self.gr_vector_to_stream_0_0_0, 0),
(self.wxgui_scopesink2_0_1_0_0, 0))
self.connect((self.gr_vector_to_stream_0_0, 0),
(self.wxgui_scopesink2_0_1_0, 0))
self.connect((self.gr_fft_vxx_0, 0), (self.gr_vector_to_stream_0, 0))
self.connect((self.gr_vector_to_stream_0, 0),
(self.gr_keep_m_in_n_0, 0))
self.connect((self.gr_stream_to_vector_0_0, 0),
(self.gr_deinterleave_0, 0))
self.connect((self.gr_stream_to_vector_0, 0), (self.gr_fft_vxx_0, 0))
self.connect((self.gr_vector_to_stream_0_0_1, 0),
(self.wxgui_scopesink2_0_1_0_1, 0))
self.connect((self.gr_vector_to_stream_0_0_1_0, 0),
(self.wxgui_scopesink2_0_1_0_1, 1))
self.connect((self.gr_vector_source_x_0_0_0, 0),
(self.gr_vector_to_stream_0_0_1_0, 0))
self.connect((self.pss_chan_est2_0, 0), (self.gr_multiply_xx_1, 1))
self.connect((self.gr_multiply_xx_1, 0), (self.sss_ml_fd_0, 0))
self.connect((self.gr_multiply_xx_1, 0),
(self.gr_vector_to_stream_0_0, 0))
self.connect((self.pss_chan_est2_0, 0), (self.gr_multiply_xx_1_0, 0))
self.connect((self.gr_deinterleave_0, 1), (self.gr_multiply_xx_1_0, 1))
self.connect((self.gr_multiply_xx_1_0, 0),
(self.gr_vector_to_stream_0_0_1, 0))
self.connect((self.gr_deinterleave_0, 1), (self.pss_chan_est2_0, 0))
self.connect((self.gr_vector_to_stream_0, 0),
(self.gr_keep_m_in_n_0_0, 0))
self.connect((self.gr_keep_m_in_n_0_0, 0), (self.gr_stream_mux_0, 0))
self.connect((self.gr_keep_m_in_n_0, 0), (self.gr_stream_mux_0, 1))
self.connect((self.gr_stream_mux_0, 0),
(self.gr_stream_to_vector_0_0, 0))
self.connect((self.gr_throttle_0, 0), (self.gr_stream_to_vector_0, 0))
self.connect((self.gr_null_source_0, 0), (self.blks2_selector_0, 1))
self.connect((self.gr_null_source_0, 0), (self.blks2_selector_0, 2))
self.connect((self.sss_ml_fd_0, 0), (self.wxgui_scopesink2_0_1, 0))
self.connect((self.gr_deinterleave_0, 0), (self.gr_multiply_xx_1, 0))
def __init__(self):
grc_wxgui.top_block_gui.__init__(self, title="Top Block")
_icon_path = "/usr/share/icons/hicolor/32x32/apps/gnuradio-grc.png"
self.SetIcon(wx.Icon(_icon_path, wx.BITMAP_TYPE_ANY))
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 192000
self.Noise = Noise = 0.01
self.Loudness = Loudness = 0.7
self.Frequency = Frequency = 5000
##################################################
# Blocks
##################################################
_Noise_sizer = wx.BoxSizer(wx.VERTICAL)
self._Noise_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_Noise_sizer,
value=self.Noise,
callback=self.set_Noise,
label="Noise",
converter=forms.float_converter(),
proportion=0,
)
self._Noise_slider = forms.slider(
parent=self.GetWin(),
sizer=_Noise_sizer,
value=self.Noise,
callback=self.set_Noise,
minimum=0.0,
maximum=1,
num_steps=1000,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_Noise_sizer)
_Loudness_sizer = wx.BoxSizer(wx.VERTICAL)
self._Loudness_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_Loudness_sizer,
value=self.Loudness,
callback=self.set_Loudness,
label="Loudness",
converter=forms.float_converter(),
proportion=0,
)
self._Loudness_slider = forms.slider(
parent=self.GetWin(),
sizer=_Loudness_sizer,
value=self.Loudness,
callback=self.set_Loudness,
minimum=0.0,
maximum=1.0,
num_steps=1000,
style=wx.SL_HORIZONTAL,
cast=float,
proportion=1,
)
self.Add(_Loudness_sizer)
_Frequency_sizer = wx.BoxSizer(wx.VERTICAL)
self._Frequency_text_box = forms.text_box(
parent=self.GetWin(),
sizer=_Frequency_sizer,
value=self.Frequency,
callback=self.set_Frequency,
label="Frequency",
converter=forms.int_converter(),
proportion=0,
)
self._Frequency_slider = forms.slider(
parent=self.GetWin(),
sizer=_Frequency_sizer,
value=self.Frequency,
callback=self.set_Frequency,
minimum=10,
maximum=20000,
num_steps=1000,
style=wx.SL_HORIZONTAL,
cast=int,
proportion=1,
)
self.Add(_Frequency_sizer)
self.wxgui_waterfallsink2_0 = waterfallsink2.waterfall_sink_c(
self.GetWin(),
baseband_freq=0,
dynamic_range=100,
ref_level=0,
ref_scale=4.0,
sample_rate=samp_rate,
fft_size=2048,
fft_rate=15,
average=False,
avg_alpha=0.1,
title="Waterfall Plot",
size=(900,200),
)
self.Add(self.wxgui_waterfallsink2_0.win)
def wxgui_waterfallsink2_0_callback(x, y):
self.set_Frequency(x)
self.wxgui_waterfallsink2_0.set_callback(wxgui_waterfallsink2_0_callback)
self.wxgui_fftsink2_0 = fftsink2.fft_sink_c(
self.GetWin(),
baseband_freq=0,
y_per_div=10,
y_divs=10,
ref_level=0,
ref_scale=4.0,
sample_rate=samp_rate,
fft_size=2048,
fft_rate=15,
average=True,
avg_alpha=0.1,
title="FFT Plot",
peak_hold=True,
)
self.Add(self.wxgui_fftsink2_0.win)
self.gr_sig_source_x_2 = gr.sig_source_c(samp_rate, gr.GR_SIN_WAVE, Frequency, Loudness, 0)
self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN, Noise, 0)
self.gr_complex_to_real_0 = gr.complex_to_real(1)
self.gr_add_xx_1 = gr.add_vcc(1)
self.audio_sink_0 = audio.sink(samp_rate, "", True)
##################################################
# Connections
##################################################
self.connect((self.gr_complex_to_real_0, 0), (self.audio_sink_0, 0))
self.connect((self.gr_noise_source_x_0, 0), (self.gr_add_xx_1, 0))
self.connect((self.gr_sig_source_x_2, 0), (self.gr_add_xx_1, 1))
self.connect((self.gr_add_xx_1, 0), (self.gr_complex_to_real_0, 0))
self.connect((self.gr_add_xx_1, 0), (self.wxgui_waterfallsink2_0, 0))
self.connect((self.gr_add_xx_1, 0), (self.wxgui_fftsink2_0, 0))
def __init__(self):
gr.top_block.__init__(self, "Simple QAM Simulation")
Qt.QWidget.__init__(self)
self.setWindowTitle("Simple QAM Simulation")
self.setWindowIcon(Qt.QIcon.fromTheme('gnuradio-grc'))
self.top_scroll_layout = Qt.QVBoxLayout()
self.setLayout(self.top_scroll_layout)
self.top_scroll = Qt.QScrollArea()
self.top_scroll.setFrameStyle(Qt.QFrame.NoFrame)
self.top_scroll_layout.addWidget(self.top_scroll)
self.top_scroll.setWidgetResizable(True)
self.top_widget = Qt.QWidget()
self.top_scroll.setWidget(self.top_widget)
self.top_layout = Qt.QVBoxLayout(self.top_widget)
self.top_grid_layout = Qt.QGridLayout()
self.top_layout.addLayout(self.top_grid_layout)
##################################################
# Variables
##################################################
self.constellation_cardinality = constellation_cardinality = 16
self.const_object = const_object = constellations()['qam'](
constellation_cardinality)
self.snr_db = snr_db = 20
self.constellation = constellation = const_object.points()
self.sps = sps = 8
self.samp_rate = samp_rate = 250000
self.noise_amp = noise_amp = sqrt((10**(-snr_db / 10.)) / 2.)
self.constellation_power = constellation_power = sqrt(
sum([abs(i)**2
for i in constellation]) / constellation_cardinality)
##################################################
# Blocks
##################################################
self.tabid_0 = Qt.QTabWidget()
self.tabid_0_widget_0 = Qt.QWidget()
self.tabid_0_layout_0 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_0_widget_0)
self.tabid_0_grid_layout_0 = Qt.QGridLayout()
self.tabid_0_layout_0.addLayout(self.tabid_0_grid_layout_0)
self.tabid_0.addTab(self.tabid_0_widget_0, "TX")
self.tabid_0_widget_1 = Qt.QWidget()
self.tabid_0_layout_1 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_0_widget_1)
self.tabid_0_grid_layout_1 = Qt.QGridLayout()
self.tabid_0_layout_1.addLayout(self.tabid_0_grid_layout_1)
self.tabid_0.addTab(self.tabid_0_widget_1, "CHANNEL")
self.tabid_0_widget_2 = Qt.QWidget()
self.tabid_0_layout_2 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_0_widget_2)
self.tabid_0_grid_layout_2 = Qt.QGridLayout()
self.tabid_0_layout_2.addLayout(self.tabid_0_grid_layout_2)
self.tabid_0.addTab(self.tabid_0_widget_2, "RX")
self.top_grid_layout.addWidget(self.tabid_0, 30, 0, 10, 100)
self.tabid_2 = Qt.QTabWidget()
self.tabid_2_widget_0 = Qt.QWidget()
self.tabid_2_layout_0 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_2_widget_0)
self.tabid_2_grid_layout_0 = Qt.QGridLayout()
self.tabid_2_layout_0.addLayout(self.tabid_2_grid_layout_0)
self.tabid_2.addTab(self.tabid_2_widget_0, "symbol-based")
self.tabid_2_widget_1 = Qt.QWidget()
self.tabid_2_layout_1 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_2_widget_1)
self.tabid_2_grid_layout_1 = Qt.QGridLayout()
self.tabid_2_layout_1.addLayout(self.tabid_2_grid_layout_1)
self.tabid_2.addTab(self.tabid_2_widget_1, "bit-based")
self.tabid_2_widget_2 = Qt.QWidget()
self.tabid_2_layout_2 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_2_widget_2)
self.tabid_2_grid_layout_2 = Qt.QGridLayout()
self.tabid_2_layout_2.addLayout(self.tabid_2_grid_layout_2)
self.tabid_2.addTab(self.tabid_2_widget_2, "BER")
self.tabid_0_layout_2.addWidget(self.tabid_2)
self.tabid_1 = Qt.QTabWidget()
self.tabid_1_widget_0 = Qt.QWidget()
self.tabid_1_layout_0 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_1_widget_0)
self.tabid_1_grid_layout_0 = Qt.QGridLayout()
self.tabid_1_layout_0.addLayout(self.tabid_1_grid_layout_0)
self.tabid_1.addTab(self.tabid_1_widget_0, "bit-based")
self.tabid_1_widget_1 = Qt.QWidget()
self.tabid_1_layout_1 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_1_widget_1)
self.tabid_1_grid_layout_1 = Qt.QGridLayout()
self.tabid_1_layout_1.addLayout(self.tabid_1_grid_layout_1)
self.tabid_1.addTab(self.tabid_1_widget_1, "scrambled")
self.tabid_1_widget_2 = Qt.QWidget()
self.tabid_1_layout_2 = Qt.QBoxLayout(Qt.QBoxLayout.TopToBottom,
self.tabid_1_widget_2)
self.tabid_1_grid_layout_2 = Qt.QGridLayout()
self.tabid_1_layout_2.addLayout(self.tabid_1_grid_layout_2)
self.tabid_1.addTab(self.tabid_1_widget_2, "symbol-based")
self.tabid_0_grid_layout_0.addWidget(self.tabid_1, 0, 0, 10, 10)
self.qtgui_time_sink_x_0 = qtgui.time_sink_f(
1024, #size
samp_rate, #bw
"QT GUI Plot", #name
1 #number of inputs
)
self._qtgui_time_sink_x_0_win = sip.wrapinstance(
self.qtgui_time_sink_x_0.pyqwidget(), Qt.QWidget)
self.tabid_2_layout_2.addWidget(self._qtgui_time_sink_x_0_win)
self.qtgui_sink_x_0_1_0_0 = qtgui.sink_f(
1024, #fftsize
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"QT GUI Plot", #name
False, #plotfreq
False, #plotwaterfall
True, #plottime
True, #plotconst
)
self._qtgui_sink_x_0_1_0_0_win = sip.wrapinstance(
self.qtgui_sink_x_0_1_0_0.pyqwidget(), Qt.QWidget)
self.tabid_1_layout_0.addWidget(self._qtgui_sink_x_0_1_0_0_win)
self.qtgui_sink_x_0_1_0 = qtgui.sink_f(
1024, #fftsize
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"QT GUI Plot", #name
True, #plotfreq
False, #plotwaterfall
True, #plottime
True, #plotconst
)
self._qtgui_sink_x_0_1_0_win = sip.wrapinstance(
self.qtgui_sink_x_0_1_0.pyqwidget(), Qt.QWidget)
self.tabid_1_layout_1.addWidget(self._qtgui_sink_x_0_1_0_win)
self.qtgui_sink_x_0_1 = qtgui.sink_c(
1024, #fftsize
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"QT GUI Plot", #name
False, #plotfreq
False, #plotwaterfall
True, #plottime
True, #plotconst
)
self._qtgui_sink_x_0_1_win = sip.wrapinstance(
self.qtgui_sink_x_0_1.pyqwidget(), Qt.QWidget)
self.tabid_1_layout_2.addWidget(self._qtgui_sink_x_0_1_win)
self.qtgui_sink_x_0_0_0_0 = qtgui.sink_c(
1024, #fftsize
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"QT GUI Plot", #name
True, #plotfreq
False, #plotwaterfall
True, #plottime
True, #plotconst
)
self._qtgui_sink_x_0_0_0_0_win = sip.wrapinstance(
self.qtgui_sink_x_0_0_0_0.pyqwidget(), Qt.QWidget)
self.tabid_2_layout_0.addWidget(self._qtgui_sink_x_0_0_0_0_win)
self.qtgui_sink_x_0_0_0 = qtgui.sink_f(
1024, #fftsize
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"QT GUI Plot", #name
False, #plotfreq
False, #plotwaterfall
True, #plottime
True, #plotconst
)
self._qtgui_sink_x_0_0_0_win = sip.wrapinstance(
self.qtgui_sink_x_0_0_0.pyqwidget(), Qt.QWidget)
self.tabid_2_layout_1.addWidget(self._qtgui_sink_x_0_0_0_win)
self.qtgui_sink_x_0_0 = qtgui.sink_c(
1024, #fftsize
firdes.WIN_BLACKMAN_hARRIS, #wintype
0, #fc
samp_rate, #bw
"QT GUI Plot", #name
True, #plotfreq
False, #plotwaterfall
True, #plottime
False, #plotconst
)
self._qtgui_sink_x_0_0_win = sip.wrapinstance(
self.qtgui_sink_x_0_0.pyqwidget(), Qt.QWidget)
self.tabid_0_layout_1.addWidget(self._qtgui_sink_x_0_0_win)
self.gr_vector_source_x_0_0 = gr.vector_source_b(([1, 0]), True, 1)
self.gr_vector_source_x_0 = gr.vector_source_b(([1, 0]), True, 1)
self.gr_unpack_k_bits_bb_0 = gr.unpack_k_bits_bb(
int(log2(constellation_cardinality)))
self.gr_throttle_0 = gr.throttle(gr.sizeof_gr_complex * 1, samp_rate)
self.gr_pack_k_bits_bb_0 = gr.pack_k_bits_bb(
int(log2(constellation_cardinality)))
self.gr_null_sink_0 = gr.null_sink(gr.sizeof_char * 1)
self.gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN, noise_amp,
0)
self.gr_nlog10_ff_0 = gr.nlog10_ff(1, 1, 0)
self.gr_multiply_const_vxx_0_0 = gr.multiply_const_vcc(
(1. / constellation_power, ))
self.gr_multiply_const_vxx_0 = gr.multiply_const_vcc(
(constellation_power, ))
self.gr_file_sink_0_1_0 = gr.file_sink(gr.sizeof_gr_complex * 1,
"rx_sym.32fc")
self.gr_file_sink_0_1_0.set_unbuffered(False)
self.gr_file_sink_0_1 = gr.file_sink(gr.sizeof_gr_complex * 1,
"tx_sym.32fc")
self.gr_file_sink_0_1.set_unbuffered(False)
self.gr_file_sink_0_0 = gr.file_sink(gr.sizeof_char * 1, "rx.8b")
self.gr_file_sink_0_0.set_unbuffered(False)
self.gr_file_sink_0 = gr.file_sink(gr.sizeof_char * 1, "tx.8b")
self.gr_file_sink_0.set_unbuffered(False)
self.gr_descrambler_bb_0 = gr.descrambler_bb(0xe4001, 0x7ffff, 19)
self.gr_char_to_float_1_0 = gr.char_to_float(1, 1)
self.gr_char_to_float_1 = gr.char_to_float(1, 1)
self.gr_char_to_float_0 = gr.char_to_float(1, 1)
self.gr_add_xx_0 = gr.add_vcc(1)
self.digital_scrambler_bb_0 = digital.scrambler_bb(
0xe4001, 0x7fffF, 19)
self.digital_constellation_receiver_cb_0 = digital.constellation_receiver_cb(
const_object.base(), 6.28 / 100, -0.25, +0.25)
self.digital_chunks_to_symbols_xx_0 = digital.chunks_to_symbols_bc(
(constellation), 1)
self.blks2_error_rate_0 = grc_blks2.error_rate(
type='BER',
win_size=samp_rate,
bits_per_symbol=1,
)
##################################################
# Connections
##################################################
self.connect((self.gr_vector_source_x_0, 0),
(self.digital_scrambler_bb_0, 0))
self.connect((self.digital_scrambler_bb_0, 0),
(self.gr_pack_k_bits_bb_0, 0))
self.connect((self.gr_pack_k_bits_bb_0, 0),
(self.digital_chunks_to_symbols_xx_0, 0))
self.connect((self.digital_constellation_receiver_cb_0, 0),
(self.gr_file_sink_0_0, 0))
self.connect((self.digital_constellation_receiver_cb_0, 0),
(self.gr_unpack_k_bits_bb_0, 0))
self.connect((self.gr_unpack_k_bits_bb_0, 0),
(self.gr_descrambler_bb_0, 0))
self.connect((self.gr_descrambler_bb_0, 0), (self.gr_null_sink_0, 0))
self.connect((self.gr_multiply_const_vxx_0, 0),
(self.digital_constellation_receiver_cb_0, 0))
self.connect((self.gr_descrambler_bb_0, 0),
(self.gr_char_to_float_0, 0))
self.connect((self.gr_char_to_float_0, 0),
(self.qtgui_sink_x_0_0_0, 0))
self.connect((self.gr_add_xx_0, 0), (self.gr_throttle_0, 0))
self.connect((self.gr_noise_source_x_0, 0), (self.gr_add_xx_0, 1))
self.connect((self.digital_chunks_to_symbols_xx_0, 0),
(self.gr_multiply_const_vxx_0_0, 0))
self.connect((self.gr_multiply_const_vxx_0_0, 0),
(self.gr_file_sink_0_1, 0))
self.connect((self.gr_multiply_const_vxx_0_0, 0),
(self.qtgui_sink_x_0_1, 0))
self.connect((self.gr_char_to_float_1, 0),
(self.qtgui_sink_x_0_1_0, 0))
self.connect((self.gr_pack_k_bits_bb_0, 0),
(self.gr_char_to_float_1, 0))
self.connect((self.gr_pack_k_bits_bb_0, 0), (self.gr_file_sink_0, 0))
self.connect((self.gr_char_to_float_1_0, 0),
(self.qtgui_sink_x_0_1_0_0, 0))
self.connect((self.gr_vector_source_x_0, 0),
(self.gr_char_to_float_1_0, 0))
self.connect((self.gr_multiply_const_vxx_0_0, 0),
(self.gr_add_xx_0, 0))
self.connect((self.gr_add_xx_0, 0), (self.qtgui_sink_x_0_0, 0))
self.connect((self.gr_throttle_0, 0),
(self.gr_multiply_const_vxx_0, 0))
self.connect((self.gr_throttle_0, 0), (self.gr_file_sink_0_1_0, 0))
self.connect((self.gr_throttle_0, 0), (self.qtgui_sink_x_0_0_0_0, 0))
self.connect((self.gr_nlog10_ff_0, 0), (self.qtgui_time_sink_x_0, 0))
self.connect((self.blks2_error_rate_0, 0), (self.gr_nlog10_ff_0, 0))
self.connect((self.gr_vector_source_x_0_0, 0),
(self.blks2_error_rate_0, 0))
self.connect((self.gr_descrambler_bb_0, 0),
(self.blks2_error_rate_0, 1))
def main():
N = 1000000
fs = 8000
freqs = [100, 200, 300, 400, 500]
nchans = 7
sigs = list()
fmtx = list()
for fi in freqs:
s = gr.sig_source_f(fs, gr.GR_SIN_WAVE, fi, 1)
fm = blks2.nbfm_tx (fs, 4*fs, max_dev=10000, tau=75e-6)
sigs.append(s)
fmtx.append(fm)
syntaps = gr.firdes.low_pass_2(len(freqs), fs, fs/float(nchans)/2, 100, 100)
print "Synthesis Num. Taps = %d (taps per filter = %d)" % (len(syntaps),
len(syntaps)/nchans)
chtaps = gr.firdes.low_pass_2(len(freqs), fs, fs/float(nchans)/2, 100, 100)
print "Channelizer Num. Taps = %d (taps per filter = %d)" % (len(chtaps),
len(chtaps)/nchans)
filtbank = gr.pfb_synthesizer_ccf(nchans, syntaps)
channelizer = blks2.pfb_channelizer_ccf(nchans, chtaps)
noise_level = 0.01
head = gr.head(gr.sizeof_gr_complex, N)
noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_level)
addnoise = gr.add_cc()
snk_synth = gr.vector_sink_c()
tb = gr.top_block()
tb.connect(noise, (addnoise,0))
tb.connect(filtbank, head, (addnoise, 1))
tb.connect(addnoise, channelizer)
tb.connect(addnoise, snk_synth)
snk = list()
for i,si in enumerate(sigs):
tb.connect(si, fmtx[i], (filtbank, i))
for i in xrange(nchans):
snk.append(gr.vector_sink_c())
tb.connect((channelizer, i), snk[i])
tb.run()
if 1:
channel = 1
data = snk[channel].data()[1000:]
f1 = pylab.figure(1)
s1 = f1.add_subplot(1,1,1)
s1.plot(data[10000:10200] )
s1.set_title(("Output Signal from Channel %d" % channel))
fftlen = 2048
winfunc = scipy.blackman
#winfunc = scipy.hamming
f2 = pylab.figure(2)
s2 = f2.add_subplot(1,1,1)
s2.psd(data, NFFT=fftlen,
Fs = nchans*fs,
noverlap=fftlen/4,
window = lambda d: d*winfunc(fftlen))
s2.set_title(("Output PSD from Channel %d" % channel))
f3 = pylab.figure(3)
s3 = f3.add_subplot(1,1,1)
s3.psd(snk_synth.data()[1000:], NFFT=fftlen,
Fs = nchans*fs,
noverlap=fftlen/4,
window = lambda d: d*winfunc(fftlen))
s3.set_title("Output of Synthesis Filter")
pylab.show()
# set up some common es components
arb = es.es_make_arbiter()
queue = es.queue()
# most packets will got out as scheduled
# but if we are ever later just send it as soon as possible
queue.set_early_behavior(1)
#queue.set_early_behavior(0);
# set up the main flow graph
tb = gr.top_block()
src = es.source(arb, queue, [gr.sizeof_gr_complex])
#sink = gr.file_sink(gr.sizeof_gr_complex , "outfile.dat" );
sink = gr.udp_sink(gr.sizeof_gr_complex, "localhost", 12345)
summer = gr.add_cc()
noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_amp)
throttle = gr.throttle(gr.sizeof_gr_complex, fs)
tb.connect(src, summer, sink)
tb.connect(noise, throttle, (summer, 1))
# create initial event, set up event bindings, handlers
e1 = es.event_create("burst_transmit", 10, 1000)
e1 = es.event_args_add(e1, key_sym, pmt.intern("1"))
queue.register_event_type(es.event_type(e1))
queue.bind_handler(es.event_type(e1), es.make_handler_pmt(key_handler_graph))
# start the main flowgraph
tb.start()
import Tkinter as tk
import sys
def run_test(seed, blocksize):
tb = gr.top_block()
##################################################
# Variables
##################################################
M = 2
K = 1
P = 2
h = (1.0 * K) / P
L = 3
Q = 4
frac = 0.99
f = trellis.fsm(P, M, L)
# CPFSK signals
#p = numpy.ones(Q)/(2.0)
#q = numpy.cumsum(p)/(1.0*Q)
# GMSK signals
BT = 0.3
tt = numpy.arange(0, L * Q) / (1.0 * Q) - L / 2.0
#print tt
p = (0.5 * scipy.stats.erfc(2 * math.pi * BT * (tt - 0.5) / math.sqrt(
math.log(2.0)) / math.sqrt(2.0)) - 0.5 * scipy.stats.erfc(
2 * math.pi * BT *
(tt + 0.5) / math.sqrt(math.log(2.0)) / math.sqrt(2.0))) / 2.0
p = p / sum(p) * Q / 2.0
#print p
q = numpy.cumsum(p) / Q
q = q / q[-1] / 2.0
#print q
(f0T, SS, S, F, Sf, Ff,
N) = fsm_utils.make_cpm_signals(K, P, M, L, q, frac)
#print N
#print Ff
Ffa = numpy.insert(Ff, Q, numpy.zeros(N), axis=0)
#print Ffa
MF = numpy.fliplr(numpy.transpose(Ffa))
#print MF
E = numpy.sum(numpy.abs(Sf)**2, axis=0)
Es = numpy.sum(E) / f.O()
#print Es
constellation = numpy.reshape(numpy.transpose(Sf), N * f.O())
#print Ff
#print Sf
#print constellation
#print numpy.max(numpy.abs(SS - numpy.dot(Ff , Sf)))
EsN0_db = 10.0
N0 = Es * 10.0**(-(1.0 * EsN0_db) / 10.0)
#N0 = 0.0
#print N0
head = 4
tail = 4
numpy.random.seed(seed * 666)
data = numpy.random.randint(0, M, head + blocksize + tail + 1)
#data = numpy.zeros(blocksize+1+head+tail,'int')
for i in range(head):
data[i] = 0
for i in range(tail + 1):
data[-i] = 0
##################################################
# Blocks
##################################################
random_source_x_0 = gr.vector_source_b(data.tolist(), False)
gr_chunks_to_symbols_xx_0 = gr.chunks_to_symbols_bf((-1, 1), 1)
gr_interp_fir_filter_xxx_0 = gr.interp_fir_filter_fff(Q, p)
gr_frequency_modulator_fc_0 = gr.frequency_modulator_fc(2 * math.pi * h *
(1.0 / Q))
gr_add_vxx_0 = gr.add_vcc(1)
gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN, (N0 / 2.0)**0.5,
-long(seed))
gr_multiply_vxx_0 = gr.multiply_vcc(1)
gr_sig_source_x_0 = gr.sig_source_c(Q, gr.GR_COS_WAVE, -f0T, 1, 0)
# only works for N=2, do it manually for N>2...
gr_fir_filter_xxx_0_0 = gr.fir_filter_ccc(Q, MF[0].conjugate())
gr_fir_filter_xxx_0_0_0 = gr.fir_filter_ccc(Q, MF[1].conjugate())
gr_streams_to_stream_0 = gr.streams_to_stream(gr.sizeof_gr_complex * 1,
int(N))
gr_skiphead_0 = gr.skiphead(gr.sizeof_gr_complex * 1, int(N * (1 + 0)))
viterbi = trellis.viterbi_combined_cb(f, head + blocksize + tail, 0, -1,
int(N), constellation,
digital.TRELLIS_EUCLIDEAN)
gr_vector_sink_x_0 = gr.vector_sink_b()
##################################################
# Connections
##################################################
tb.connect((random_source_x_0, 0), (gr_chunks_to_symbols_xx_0, 0))
tb.connect((gr_chunks_to_symbols_xx_0, 0), (gr_interp_fir_filter_xxx_0, 0))
tb.connect((gr_interp_fir_filter_xxx_0, 0),
(gr_frequency_modulator_fc_0, 0))
tb.connect((gr_frequency_modulator_fc_0, 0), (gr_add_vxx_0, 0))
tb.connect((gr_noise_source_x_0, 0), (gr_add_vxx_0, 1))
tb.connect((gr_add_vxx_0, 0), (gr_multiply_vxx_0, 0))
tb.connect((gr_sig_source_x_0, 0), (gr_multiply_vxx_0, 1))
tb.connect((gr_multiply_vxx_0, 0), (gr_fir_filter_xxx_0_0, 0))
tb.connect((gr_multiply_vxx_0, 0), (gr_fir_filter_xxx_0_0_0, 0))
tb.connect((gr_fir_filter_xxx_0_0, 0), (gr_streams_to_stream_0, 0))
tb.connect((gr_fir_filter_xxx_0_0_0, 0), (gr_streams_to_stream_0, 1))
tb.connect((gr_streams_to_stream_0, 0), (gr_skiphead_0, 0))
tb.connect((gr_skiphead_0, 0), (viterbi, 0))
tb.connect((viterbi, 0), (gr_vector_sink_x_0, 0))
tb.run()
dataest = gr_vector_sink_x_0.data()
#print data
#print numpy.array(dataest)
perr = 0
err = 0
for i in range(blocksize):
if data[head + i] != dataest[head + i]:
#print i
err += 1
if err != 0:
perr = 1
return (err, perr)
