def __init__(self, N=512 , NW=3 , K=5, weighting='adaptive', fftshift=False):
gr.hier_block2.__init__(self, "mtm",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float*N))
self.check_parameters(N, NW, K)
self.s2v = gr.stream_to_vector(gr.sizeof_gr_complex, N)
self.connect(self, self.s2v)
dpss = specest_gendpss.gendpss(N=N, NW=NW, K=K)
self.mtm = [eigenspectrum(dpss.dpssarray[i], fftshift) for i in xrange(K)]
if weighting == 'adaptive':
self.sum = specest_swig.adaptiveweighting_vff(N, dpss.lambdas)
self.connect_mtm(K)
self.connect(self.sum, self)
elif weighting == 'unity':
self.sum = gr.add_ff(N)
self.divide = gr.multiply_const_vff([1./K]*N)
self.connect_mtm(K)
self.connect(self.sum, self.divide, self)
elif weighting == 'eigenvalues':
self.eigvalmulti = []
self.lambdasum = 0
for i in xrange(K):
self.eigvalmulti.append(gr.multiply_const_vff([dpss.lambdas[i]]*N))
self.lambdasum += dpss.lambdas[i]
self.divide = gr.multiply_const_vff([1./self.lambdasum]*N)
self.sum = gr.add_ff(N)
self.connect_mtm(K)
self.connect(self.sum, self.divide, self)
else:
raise ValueError, 'weighting-type should be: adaptive, unity or eigenvalues'
def __init__(self, N=512 , NW=3 , K=5, weighting='adaptive', fftshift=False):
gr.hier_block2.__init__(self, "mtm",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float*N))
self.check_parameters(N, NW, K)
self.s2v = gr.stream_to_vector(gr.sizeof_gr_complex, N)
self.connect(self, self.s2v)
dpss = specest_gendpss.gendpss(N=N, NW=NW, K=K)
self.mtm = [eigenspectrum(dpss.dpssarray[i], fftshift) for i in xrange(K)]
if weighting == 'adaptive':
self.sum = specest_swig.adaptiveweighting_vff(N, dpss.lambdas)
self.connect_mtm(K)
self.connect(self.sum, self)
elif weighting == 'unity':
self.sum = gr.add_ff(N)
self.divide = gr.multiply_const_vff([1./K]*N)
self.connect_mtm(K)
self.connect(self.sum, self.divide, self)
elif weighting == 'eigenvalues':
self.eigvalmulti = []
self.lambdasum = 0
for i in xrange(K):
self.eigvalmulti.append(gr.multiply_const_vff([dpss.lambdas[i]]*N))
self.lambdasum += dpss.lambdas[i]
self.divide = gr.multiply_const_vff([1./self.lambdasum]*N)
self.sum = gr.add_ff(N)
self.connect_mtm(K)
self.connect(self.sum, self.divide, self)
else:
raise ValueError, 'weighting-type should be: adaptive, unity or eigenvalues'
def __init__(self, fd, M, sample_rate):
gr.hier_block2.__init__(self, "Rayleigh Channel",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
self.M = M
self.sample_rate = sample_rate
n = range(1, M + 1)
N = 4 * M + 2
f_n = [fd * math.cos(2 * math.pi * x / N) for x in n]
beta_n = [math.pi / M * x for x in n]
a_n = [2 * math.cos(x) for x in beta_n]
a_n.append(math.sqrt(2) * math.cos(math.pi / 4))
a_n = [x * 2 / math.sqrt(N) for x in a_n]
b_n = [2 * math.sin(x) for x in beta_n]
b_n.append(math.sqrt(2) * math.sin(math.pi / 4))
b_n = [x * 2 / math.sqrt(N) for x in b_n]
f_n.append(fd)
self.sin_real = [
gr.sig_source_f(self.sample_rate, gr.GR_COS_WAVE, f_n[i], a_n[i])
for i in range(M + 1)
]
self.sin_imag = [
gr.sig_source_f(self.sample_rate, gr.GR_COS_WAVE, f_n[i], b_n[i])
for i in range(M + 1)
]
self.add_real = gr.add_ff(1)
self.add_imag = gr.add_ff(1)
for i in range(M + 1):
self.connect(self.sin_real[i], (self.add_real, i))
for i in range(M + 1):
self.connect(self.sin_imag[i], (self.add_imag, i))
self.ftoc = gr.float_to_complex(1)
self.connect(self.add_real, (self.ftoc, 0))
self.connect(self.add_imag, (self.ftoc, 1))
self.mulc = gr.multiply_const_cc((0.5))
#self.divide = gr.divide_cc(1)
#self.connect(self,(self.divide,0))
#self.connect(self.ftoc,(self.divide,1))
#self.connect(self.divide, self)
self.prod = gr.multiply_cc(1)
self.connect(self, (self.prod, 0))
self.connect(self.ftoc, self.mulc, (self.prod, 1))
self.connect(self.prod, self)
def _get_gauss_rand_proc_c(self):
""" Returns the Gaussian random process.
"""
spec_getter = getattr(self.model, 'get_' + self.spec_type)
if self.spec_type in self.model.specs_odd:
from winelo.channel import spec2soc
soc = spec2soc(spec_getter(), method=self.method, N=self.N)
sources = []
adder = gr.add_cc()
for idx, (freq, ampl) in enumerate(soc.get_soc()):
sources.append(gr.sig_source_c(self.sample_rate,
gr.GR_COS_WAVE, freq, ampl))
self.connect(sources[idx],
gr.skiphead(gr.sizeof_gr_complex,
randint(low=0, high=self.sample_rate)),
(adder, idx))
return adder
elif self.spec_type in self.model.specs_even:
from winelo.channel import spec2sos
# real part of the gaussian random process
sos_real = spec2sos(spec_getter(), method=self.method, N=self.N)
sources_real = []
adder_real = gr.add_ff()
for idx, (freq, ampl) in enumerate(sos_real.get_sos()):
sources_real.append(gr.sig_source_f(self.sample_rate,
gr.GR_COS_WAVE, freq,
ampl))
self.connect(sources_real[idx],
gr.skiphead(gr.sizeof_float,
randint(low=0, high=self.sample_rate)),
(adder_real, idx))
# imaginary part of the gaussian random process
sos_imaginary = spec2sos(spec_getter(), method=self.method,
N=self.N + 1)
sources_imag = []
adder_imag = gr.add_ff()
for idx, (freq, ampl) in enumerate(sos_imaginary.get_sos()):
sources_imag.append(gr.sig_source_f(self.sample_rate,
gr.GR_COS_WAVE, freq,
ampl))
self.connect(sources_imag[idx],
gr.skiphead(gr.sizeof_float,
randint(low=0, high=self.sample_rate)),
(adder_imag, idx))
float2complex = gr.float_to_complex()
self.connect(adder_real, (float2complex, 0))
self.connect(adder_imag, (float2complex, 1))
return float2complex
else:
print 'You picked a non-existant Doppler spectrum'
print 'Pick one of the following: ', \
self.model.specs_even + self.model.specs_odd
return None
def __init__(self):
gr.top_block.__init__(self)
Rs = 8000
f1 = 100
f2 = 200
npts = 2048
self.qapp = QtGui.QApplication(sys.argv)
src1 = gr.sig_source_f(Rs, gr.GR_SIN_WAVE, f1, 0.1, 0)
src2 = gr.sig_source_f(Rs, gr.GR_SIN_WAVE, f2, 0.1, 0)
src = gr.add_ff()
thr = gr.throttle(gr.sizeof_float, 100*npts)
noise = gr.noise_source_f(gr.GR_GAUSSIAN, 0.001)
add = gr.add_ff()
self.snk1 = qtgui.time_sink_f(npts, Rs,
"Complex Time Example", 3)
self.connect(src1, (src,0))
self.connect(src2, (src,1))
self.connect(src, thr, (add,0))
self.connect(noise, (add,1))
self.connect(add, self.snk1)
self.connect(src1, (self.snk1, 1))
self.connect(src2, (self.snk1, 2))
self.ctrl_win = control_box()
self.ctrl_win.attach_signal1(src1)
self.ctrl_win.attach_signal2(src2)
# Get the reference pointer to the SpectrumDisplayForm QWidget
pyQt = self.snk1.pyqwidget()
# Wrap the pointer as a PyQt SIP object
# This can now be manipulated as a PyQt4.QtGui.QWidget
pyWin = sip.wrapinstance(pyQt, QtGui.QWidget)
# Example of using signal/slot to set the title of a curve
pyWin.connect(pyWin, QtCore.SIGNAL("setTitle(int, QString)"),
pyWin, QtCore.SLOT("setTitle(int, QString)"))
pyWin.emit(QtCore.SIGNAL("setTitle(int, QString)"), 0, "sum")
self.snk1.set_title(1, "src1")
self.snk1.set_title(2, "src2")
# Can also set the color of a curve
#self.snk1.set_color(5, "blue")
#pyWin.show()
self.main_box = dialog_box(pyWin, self.ctrl_win)
self.main_box.show()
def __init__(self,fd,M,sample_rate):
gr.hier_block2.__init__(self,"Rayleigh Channel",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_gr_complex))
self.M = M
self.sample_rate = sample_rate
n=range(1,M+1)
N = 4*M+2
f_n= [fd*math.cos(2*math.pi*x/N) for x in n]
beta_n = [math.pi/M*x for x in n]
a_n = [2*math.cos(x) for x in beta_n]
a_n.append(math.sqrt(2)*math.cos(math.pi/4))
a_n = [x*2/math.sqrt(N) for x in a_n]
b_n= [2*math.sin(x) for x in beta_n]
b_n.append(math.sqrt(2)*math.sin(math.pi/4))
b_n = [x*2/math.sqrt(N) for x in b_n]
f_n.append(fd)
self.sin_real = [gr.sig_source_f(self.sample_rate,gr.GR_COS_WAVE,f_n[i],a_n[i]) for i in range(M+1)]
self.sin_imag = [gr.sig_source_f(self.sample_rate,gr.GR_COS_WAVE,f_n[i],b_n[i]) for i in range(M+1)]
self.add_real = gr.add_ff(1)
self.add_imag = gr.add_ff(1)
for i in range (M+1):
self.connect(self.sin_real[i],(self.add_real,i))
for i in range (M+1):
self.connect(self.sin_imag[i],(self.add_imag,i))
self.ftoc = gr.float_to_complex(1)
self.connect(self.add_real,(self.ftoc,0))
self.connect(self.add_imag,(self.ftoc,1))
self.mulc = gr.multiply_const_cc((0.5))
#self.divide = gr.divide_cc(1)
#self.connect(self,(self.divide,0))
#self.connect(self.ftoc,(self.divide,1))
#self.connect(self.divide, self)
self.prod = gr.multiply_cc(1)
self.connect(self,(self.prod,0))
self.connect(self.ftoc,self.mulc,(self.prod,1))
self.connect(self.prod, self)
def run_test (f,Kb,bitspersymbol,K,dimensionality,tot_constellation,N0,seed):
tb = gr.top_block ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the FSM input cardinality
enc = trellis.encoder_ss(f,0) # initial state = 0
# essentially here we implement the combination of modulation and channel as a memoryless modulation (the memory induced by the channel is hidden in the FSM)
mod = gr.chunks_to_symbols_sf(tot_constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
metrics = trellis.metrics_f(f.O(),dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
va = trellis.viterbi_s(f,K,0,-1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s();
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics)
tb.connect (metrics,va,fsmi2s,dst)
tb.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#print ntotal,nright,runlength
return (ntotal,ntotal-nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,tot_constellation,N0,seed):
tb = gr.top_block ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the FSM input cardinality
enc = trellis.encoder_ss(f,0) # initial state = 0
# essentially here we implement the combination of modulation and channel as a memoryless modulation (the memory induced by the channel is hidden in the FSM)
mod = gr.chunks_to_symbols_sf(tot_constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
metrics = trellis.metrics_f(f.O(),dimensionality,tot_constellation,digital.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
va = trellis.viterbi_s(f,K,0,-1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s();
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics)
tb.connect (metrics,va,fsmi2s,dst)
tb.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#print ntotal,nright,runlength
return (ntotal,ntotal-nright)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,Es,N0,IT,seed):
tb = gr.top_block ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc = trellis.sccc_encoder_ss(fo,0,fi,0,interleaver,K)
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
dec = trellis.sccc_decoder_combined_fs(fo,0,-1,fi,0,-1,interleaver,K,IT,trellis.TRELLIS_MIN_SUM,dimensionality,constellation,digital.TRELLIS_EUCLIDEAN,1.0)
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
#tb.connect (src,src_head,s2fsmi,enc_out,inter,enc_in,mod)
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
#tb.connect (add,head)
#tb.connect (tail,fsmi2s,dst)
tb.connect (add,dec,fsmi2s,dst)
tb.run()
#print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def __init__( self, if_rate, af_rate ):
gr.hier_block2.__init__(self, "ssb_demod",
gr.io_signature(1,1,gr.sizeof_gr_complex),
gr.io_signature(1,1,gr.sizeof_float))
self.if_rate = int(if_rate)
self.af_rate = int(af_rate)
self.if_decim = int(if_rate / af_rate)
self.sideband = 1
self.xlate_taps = ([complex(v) for v in file('ssb_taps').readlines()])
self.audio_taps = gr.firdes.low_pass(
1.0,
self.af_rate,
3e3,
600,
gr.firdes.WIN_HAMMING )
self.xlate = gr.freq_xlating_fir_filter_ccc(
self.if_decim,
self.xlate_taps,
0,
self.if_rate )
self.split = gr.complex_to_float()
self.lpf = gr.fir_filter_fff(
1, self.audio_taps )
self.sum = gr.add_ff( )
self.am_sel = gr.multiply_const_ff( 0 )
self.sb_sel = gr.multiply_const_ff( 1 )
self.mixer = gr.add_ff()
self.am_det = gr.complex_to_mag()
self.connect(self, self.xlate)
self.connect(self.xlate, self.split)
self.connect((self.split, 0), (self.sum, 0))
self.connect((self.split, 1), (self.sum, 1))
self.connect(self.sum, self.sb_sel)
self.connect(self.xlate, self.am_det)
self.connect(self.sb_sel, (self.mixer, 0))
self.connect(self.am_det, self.am_sel)
self.connect(self.am_sel, (self.mixer, 1))
self.connect(self.mixer, self.lpf)
self.connect(self.lpf, self)
def run_test(f, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed):
tb = gr.top_block()
# TX
# packet = [0]*Kb
# for i in range(Kb-1*16): # last 16 bits = 0 to drive the final state to 0
# packet[i] = random.randint(0, 1) # random 0s and 1s
# src = gr.vector_source_s(packet,False)
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
# b2s = gr.unpacked_to_packed_ss(1,gr.GR_MSB_FIRST) # pack bits in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the FSM input cardinality
enc = trellis.encoder_ss(f, 0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
metrics = trellis.metrics_f(
f.O(), dimensionality, constellation, digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for Viterbi
va = trellis.viterbi_s(f, K, 0, -1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
# s2b = gr.packed_to_unpacked_ss(1,gr.GR_MSB_FIRST) # unpack shorts to bits
# dst = gr.vector_sink_s();
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc, mod)
# tb.connect (src,b2s,s2fsmi,enc,mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics)
tb.connect(metrics, va, fsmi2s, dst)
# tb.connect (metrics,va,fsmi2s,s2b,dst)
tb.run()
# A bit of cheating: run the program once and print the
# final encoder state..
# Then put it as the last argument in the viterbi block
# print "final state = " , enc.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
# ntotal = len(packet)
# if len(dst.data()) != ntotal:
# print "Error: not enough data\n"
# nright = 0;
# for i in range(ntotal):
# if packet[i]==dst.data()[i]:
# nright=nright+1
# else:
# print "Error in ", i
return (ntotal, ntotal - nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed):
tb = gr.top_block ()
# TX
#packet = [0]*Kb
#for i in range(Kb-1*16): # last 16 bits = 0 to drive the final state to 0
#packet[i] = random.randint(0, 1) # random 0s and 1s
#src = gr.vector_source_s(packet,False)
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
#b2s = gr.unpacked_to_packed_ss(1,gr.GR_MSB_FIRST) # pack bits in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the FSM input cardinality
enc = trellis.encoder_ss(f,0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
metrics = trellis.metrics_f(f.O(),dimensionality,constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
va = trellis.viterbi_s(f,K,0,-1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
#s2b = gr.packed_to_unpacked_ss(1,gr.GR_MSB_FIRST) # unpack shorts to bits
#dst = gr.vector_sink_s();
dst = gr.check_lfsr_32k_s()
tb.connect (src,src_head,s2fsmi,enc,mod)
#tb.connect (src,b2s,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics)
tb.connect (metrics,va,fsmi2s,dst)
#tb.connect (metrics,va,fsmi2s,s2b,dst)
tb.run()
# A bit of cheating: run the program once and print the
# final encoder state..
# Then put it as the last argument in the viterbi block
#print "final state = " , enc.ST()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#ntotal = len(packet)
#if len(dst.data()) != ntotal:
#print "Error: not enough data\n"
#nright = 0;
#for i in range(ntotal):
#if packet[i]==dst.data()[i]:
#nright=nright+1
#else:
#print "Error in ", i
return (ntotal,ntotal-nright)
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 __init__(self, subdev_spec, audio_input):
gr.hier_block2.__init__(
self,
"transmit_path",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
self.u = usrp.sink_c()
dac_rate = self.u.dac_rate()
self.if_rate = 320e3 # 320 kS/s
self.usrp_interp = int(dac_rate // self.if_rate)
self.u.set_interp_rate(self.usrp_interp)
self.sw_interp = 10
self.audio_rate = self.if_rate // self.sw_interp # 32 kS/s
self.audio_gain = 10
self.normal_gain = 32000
self.audio = audio.source(int(self.audio_rate), audio_input)
self.audio_amp = gr.multiply_const_ff(self.audio_gain)
lpf = gr.firdes.low_pass(
1, # gain
self.audio_rate, # sampling rate
3800, # low pass cutoff freq
300, # width of trans. band
gr.firdes.WIN_HANN) # filter type
hpf = gr.firdes.high_pass(
1, # gain
self.audio_rate, # sampling rate
325, # low pass cutoff freq
50, # width of trans. band
gr.firdes.WIN_HANN) # filter type
audio_taps = convolve(array(lpf), array(hpf))
self.audio_filt = gr.fir_filter_fff(1, audio_taps)
self.pl = blks2.ctcss_gen_f(self.audio_rate, 123.0)
self.add_pl = gr.add_ff()
self.connect(self.pl, (self.add_pl, 1))
self.fmtx = blks2.nbfm_tx(self.audio_rate, self.if_rate)
self.amp = gr.multiply_const_cc(self.normal_gain)
# determine the daughterboard subdevice we're using
if subdev_spec is None:
subdev_spec = usrp.pick_tx_subdevice(self.u)
self.u.set_mux(usrp.determine_tx_mux_value(self.u, subdev_spec))
self.subdev = usrp.selected_subdev(self.u, subdev_spec)
print "TX using", self.subdev.name()
self.connect(self.audio, self.audio_amp, self.audio_filt,
(self.add_pl, 0), self.fmtx, self.amp, self.u)
self.set_gain(self.subdev.gain_range()[1]) # set max Tx gain
def __init__( self, fg, if_rate, af_rate ):
self.if_rate = if_rate
self.af_rate = af_rate
self.if_decim = if_rate / af_rate
self.sideband = 1
self.xlate_taps = ([complex(v) for v in file('ssb_taps').readlines()])
self.audio_taps = gr.firdes.low_pass(
1.0,
self.af_rate,
3e3,
600,
gr.firdes.WIN_HAMMING )
self.xlate = gr.freq_xlating_fir_filter_ccc(
self.if_decim,
self.xlate_taps,
0,
self.if_rate )
self.split = gr.complex_to_float()
self.lpf = gr.fir_filter_fff(
1, self.audio_taps )
self.sum = gr.add_ff( )
self.am_sel = gr.multiply_const_ff( 0 )
self.sb_sel = gr.multiply_const_ff( 1 )
self.mixer = gr.add_ff()
self.am_det = gr.complex_to_mag()
fg.connect( self.xlate, self.split )
fg.connect( ( self.split,0 ), ( self.sum,0 ) )
fg.connect( ( self.split,1 ), ( self.sum,1 ) )
fg.connect( self.sum, self.sb_sel )
fg.connect( self.xlate, self.am_det )
fg.connect( self.sb_sel, ( self.mixer, 0 ) )
fg.connect( self.am_det, self.am_sel )
fg.connect( self.am_sel, ( self.mixer, 1 ) )
fg.connect( self.mixer, self.lpf )
gr.hier_block.__init__( self, fg, self.xlate, self.lpf )
def __init__(self, subdev_spec, audio_input):
gr.hier_block2.__init__(
self, "transmit_path", gr.io_signature(0, 0, 0), gr.io_signature(0, 0, 0) # Input signature
) # Output signature
self.u = usrp.sink_c()
dac_rate = self.u.dac_rate()
self.if_rate = 320e3 # 320 kS/s
self.usrp_interp = int(dac_rate // self.if_rate)
self.u.set_interp_rate(self.usrp_interp)
self.sw_interp = 10
self.audio_rate = self.if_rate // self.sw_interp # 32 kS/s
self.audio_gain = 10
self.normal_gain = 32000
self.audio = audio.source(int(self.audio_rate), audio_input)
self.audio_amp = gr.multiply_const_ff(self.audio_gain)
lpf = gr.firdes.low_pass(
1, # gain
self.audio_rate, # sampling rate
3800, # low pass cutoff freq
300, # width of trans. band
gr.firdes.WIN_HANN,
) # filter type
hpf = gr.firdes.high_pass(
1, # gain
self.audio_rate, # sampling rate
325, # low pass cutoff freq
50, # width of trans. band
gr.firdes.WIN_HANN,
) # filter type
audio_taps = convolve(array(lpf), array(hpf))
self.audio_filt = gr.fir_filter_fff(1, audio_taps)
self.pl = blks2.ctcss_gen_f(self.audio_rate, 123.0)
self.add_pl = gr.add_ff()
self.connect(self.pl, (self.add_pl, 1))
self.fmtx = blks2.nbfm_tx(self.audio_rate, self.if_rate)
self.amp = gr.multiply_const_cc(self.normal_gain)
# determine the daughterboard subdevice we're using
if subdev_spec is None:
subdev_spec = usrp.pick_tx_subdevice(self.u)
self.u.set_mux(usrp.determine_tx_mux_value(self.u, subdev_spec))
self.subdev = usrp.selected_subdev(self.u, subdev_spec)
print "TX using", self.subdev.name()
self.connect(self.audio, self.audio_amp, self.audio_filt, (self.add_pl, 0), self.fmtx, self.amp, self.u)
self.set_gain(self.subdev.gain_range()[1]) # set max Tx gain
def __init__(self):
gr.top_block.__init__(self)
Rs = 8000
f1 = 1000
f2 = 2000
fftsize = 2048
self.qapp = QtGui.QApplication(sys.argv)
src1 = gr.sig_source_f(Rs, gr.GR_SIN_WAVE, f1, 0.1, 0)
src2 = gr.sig_source_f(Rs, gr.GR_SIN_WAVE, f2, 0.1, 0)
src = gr.add_ff()
thr = gr.throttle(gr.sizeof_float, 100*fftsize)
noise = gr.noise_source_f(gr.GR_GAUSSIAN, 0.001)
add = gr.add_ff()
self.snk1 = qtgui.sink_f(fftsize, gr.firdes.WIN_BLACKMAN_hARRIS,
0, Rs,
"Float Signal Example",
True, True, True, False)
self.connect(src1, (src,0))
self.connect(src2, (src,1))
self.connect(src, thr, (add,0))
self.connect(noise, (add,1))
self.connect(add, self.snk1)
self.ctrl_win = control_box()
self.ctrl_win.attach_signal1(src1)
self.ctrl_win.attach_signal2(src2)
# Get the reference pointer to the SpectrumDisplayForm QWidget
pyQt = self.snk1.pyqwidget()
# Wrap the pointer as a PyQt SIP object
# This can now be manipulated as a PyQt4.QtGui.QWidget
pyWin = sip.wrapinstance(pyQt, QtGui.QWidget)
self.main_box = dialog_box(pyWin, self.ctrl_win)
self.main_box.show()
def __init__(self):
gr.top_block.__init__(self)
Rs = 8000
f1 = 1000
f2 = 2000
fftsize = 2048
self.qapp = QtGui.QApplication(sys.argv)
src1 = gr.sig_source_f(Rs, gr.GR_SIN_WAVE, f1, 0.1, 0)
src2 = gr.sig_source_f(Rs, gr.GR_SIN_WAVE, f2, 0.1, 0)
src = gr.add_ff()
thr = gr.throttle(gr.sizeof_float, 100*fftsize)
noise = gr.noise_source_f(gr.GR_GAUSSIAN, 0.001)
add = gr.add_ff()
self.snk1 = qtgui.sink_f(fftsize, gr.firdes.WIN_BLACKMAN_hARRIS,
0, Rs,
"Float Signal Example",
True, True, True, False)
self.connect(src1, (src,0))
self.connect(src2, (src,1))
self.connect(src, thr, (add,0))
self.connect(noise, (add,1))
self.connect(add, self.snk1)
self.ctrl_win = control_box()
self.ctrl_win.attach_signal1(src1)
self.ctrl_win.attach_signal2(src2)
# Get the reference pointer to the SpectrumDisplayForm QWidget
pyQt = self.snk1.pyqwidget()
# Wrap the pointer as a PyQt SIP object
# This can now be manipulated as a PyQt4.QtGui.QWidget
pyWin = sip.wrapinstance(pyQt, QtGui.QWidget)
self.main_box = dialog_box(pyWin, self.ctrl_win)
self.main_box.show()
def run_test(f, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed,
P):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16 * P) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the FSM input cardinality
s2p = gr.stream_to_streams(gr.sizeof_short, P) # serial to parallel
enc = trellis.encoder_ss(f, 0) # initiali state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = []
noise = []
for i in range(P):
add.append(gr.add_ff())
noise.append(gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2),
seed))
# RX
metrics = trellis.metrics_f(
f.O(), dimensionality, constellation, digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for Viterbi
va = trellis.viterbi_s(
f, K, 0, -1) # Put -1 if the Initial/Final states are not set.
p2s = gr.streams_to_stream(gr.sizeof_short, P) # parallel to serial
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, s2p)
for i in range(P):
tb.connect((s2p, i), (enc, i), (mod, i))
tb.connect((mod, i), (add[i], 0))
tb.connect(noise[i], (add[i], 1))
tb.connect(add[i], (metrics, i))
tb.connect((metrics, i), (va, i), (p2s, i))
tb.connect(p2s, fsmi2s, dst)
tb.run()
# A bit of cheating: run the program once and print the
# final encoder state.
# Then put it as the last argument in the viterbi block
#print "final state = " , enc.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def __init__(self):
gr.top_block.__init__(self, "FSK Demod Demo")
# Variables
self.symbol_rate = symbol_rate = 125e3
self.samp_rate = samp_rate = symbol_rate
self.f_center = f_center = 868e6
self.sps = sps = 2
self.sensitivity = sensitivity = (pi / 2) / sps
self.alpha = alpha = 0.0512 / sps
self.bandwidth = bandwidth = 100e3
# Blocks
self.uhd_usrp_source_0 = uhd.usrp_source(
device_addr="",
stream_args=uhd.stream_args(
cpu_format="fc32",
channels=range(1),
),
)
self.uhd_usrp_source_0.set_samp_rate(samp_rate)
self.uhd_usrp_source_0.set_center_freq(f_center, 0)
self.uhd_usrp_source_0.set_gain(0, 0)
self.uhd_usrp_source_0.set_bandwidth(bandwidth, 0)
self.fm_demod = gr.quadrature_demod_cf(1 / sensitivity)
self.freq_offset = gr.single_pole_iir_filter_ff(alpha)
self.sub = gr.sub_ff()
self.add = gr.add_ff()
self.multiply = gr.multiply_ff()
self.invert = gr.multiply_const_vff((-1, ))
# recover the clock
omega = sps
gain_mu = 0.03
mu = 0.5
omega_relative_limit = 0.0002
freq_error = 0.0
gain_omega = .25 * gain_mu * gain_mu # critically damped
self.clock_recovery = digital.clock_recovery_mm_ff(
omega, gain_omega, mu, gain_mu, omega_relative_limit)
self.slice = digital.binary_slicer_fb()
self.sink = gr.vector_sink_b(1)
self.file_sink = gr.file_sink(gr.sizeof_char, 'fsk_dump.log')
# Connections
self.connect(self.fm_demod, (self.add, 0))
self.connect(self.fm_demod, self.freq_offset, (self.add, 1))
self.connect(self.uhd_usrp_source_0, self.fm_demod)
self.connect(self.add, self.clock_recovery, self.invert, self.slice,
self.file_sink)
self.connect(self.slice, self.sink)
def run_test(f, Kb, bitspersymbol, K, channel, modulation, dimensionality,
tot_constellation, N0, seed):
tb = gr.top_block()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0] * (K + 2 * L)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
for i in range(L): # first/last L symbols set to 0
packet[i] = 0
packet[len(packet) - i - 1] = 0
src = gr.vector_source_s(packet, False)
mod = gr.chunks_to_symbols_sf(modulation[1], modulation[0])
# CHANNEL
isi = gr.fir_filter_fff(1, channel)
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
skip = gr.skiphead(
gr.sizeof_float, L
) # skip the first L samples since you know they are coming from the L zero symbols
#metrics = trellis.metrics_f(f.O(),dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
#va = trellis.viterbi_s(f,K+L,0,0) # Put -1 if the Initial/Final states are not set.
va = trellis.viterbi_combined_s(
f, K + L, 0, 0, dimensionality, tot_constellation,
trellis.TRELLIS_EUCLIDEAN
) # using viterbi_combined_s instead of metrics_f/viterbi_s allows larger packet lengths because metrics_f is complaining for not being able to allocate large buffers. This is due to the large f.O() in this application...
dst = gr.vector_sink_s()
tb.connect(src, mod)
tb.connect(mod, isi, (add, 0))
tb.connect(noise, (add, 1))
#tb.connect (add,metrics)
#tb.connect (metrics,va,dst)
tb.connect(add, skip, va, dst)
tb.run()
data = dst.data()
ntotal = len(data) - L
nright = 0
for i in range(ntotal):
if packet[i + L] == data[i]:
nright = nright + 1
#else:
#print "Error in ", i
return (ntotal, ntotal - nright)
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 __init__(self, if_rate, af_rate):
gr.hier_block2.__init__(self, "ssb_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
self.if_rate = int(if_rate)
self.af_rate = int(af_rate)
self.if_decim = int(if_rate / af_rate)
self.sideband = 1
self.xlate_taps = ([complex(v) for v in file('ssb_taps').readlines()])
self.audio_taps = gr.firdes.low_pass(1.0, self.af_rate, 3e3, 600,
gr.firdes.WIN_HAMMING)
self.xlate = gr.freq_xlating_fir_filter_ccc(self.if_decim,
self.xlate_taps, 0,
self.if_rate)
self.split = gr.complex_to_float()
self.lpf = gr.fir_filter_fff(1, self.audio_taps)
self.sum = gr.add_ff()
self.am_sel = gr.multiply_const_ff(0)
self.sb_sel = gr.multiply_const_ff(1)
self.mixer = gr.add_ff()
self.am_det = gr.complex_to_mag()
self.connect(self, self.xlate)
self.connect(self.xlate, self.split)
self.connect((self.split, 0), (self.sum, 0))
self.connect((self.split, 1), (self.sum, 1))
self.connect(self.sum, self.sb_sel)
self.connect(self.xlate, self.am_det)
self.connect(self.sb_sel, (self.mixer, 0))
self.connect(self.am_det, self.am_sel)
self.connect(self.am_sel, (self.mixer, 1))
self.connect(self.mixer, self.lpf)
self.connect(self.lpf, self)
def __init__(self): gr.top_block.__init__(self, "FSK Demod Demo") # Variables self.symbol_rate = symbol_rate = 125e3 self.samp_rate = samp_rate = symbol_rate self.f_center = f_center = 868e6 self.sps = sps = 2 self.sensitivity = sensitivity = (pi / 2) / sps self.alpha = alpha = 0.0512/sps self.bandwidth = bandwidth = 100e3 # Blocks self.uhd_usrp_source_0 = uhd.usrp_source( device_addr="", stream_args=uhd.stream_args( cpu_format="fc32", channels=range(1), ), ) self.uhd_usrp_source_0.set_samp_rate(samp_rate) self.uhd_usrp_source_0.set_center_freq(f_center, 0) self.uhd_usrp_source_0.set_gain(0, 0) self.uhd_usrp_source_0.set_bandwidth(bandwidth, 0) self.fm_demod = gr.quadrature_demod_cf(1 / sensitivity) self.freq_offset = gr.single_pole_iir_filter_ff(alpha) self.sub = gr.sub_ff() self.add = gr.add_ff() self.multiply = gr.multiply_ff() self.invert = gr.multiply_const_vff((-1, )) # recover the clock omega = sps gain_mu = 0.03 mu = 0.5 omega_relative_limit = 0.0002 freq_error = 0.0 gain_omega = .25 * gain_mu * gain_mu # critically damped self.clock_recovery = digital.clock_recovery_mm_ff(omega, gain_omega, mu, gain_mu, omega_relative_limit) self.slice = digital.binary_slicer_fb() self.sink = gr.vector_sink_b(1) self.file_sink = gr.file_sink(gr.sizeof_char, 'fsk_dump.log') # Connections self.connect(self.fm_demod, (self.add, 0)) self.connect(self.fm_demod, self.freq_offset, (self.add, 1)) self.connect(self.uhd_usrp_source_0, self.fm_demod) self.connect(self.add, self.clock_recovery, self.invert, self.slice, self.file_sink) self.connect(self.slice, self.sink)
def __init__(self, host, port, pkt_size, sample_rate, eof):
gr.top_block.__init__(self, "dial_tone_source")
amplitude = 0.3
src0 = gr.sig_source_f (sample_rate, gr.GR_SIN_WAVE, 350, amplitude)
src1 = gr.sig_source_f (sample_rate, gr.GR_SIN_WAVE, 440, amplitude)
add = gr.add_ff()
# Throttle needed here to account for the other side's audio card sampling rate
thr = gr.throttle(gr.sizeof_float, sample_rate)
sink = gr.udp_sink(gr.sizeof_float, host, port, pkt_size, eof=eof)
self.connect(src0, (add, 0))
self.connect(src1, (add, 1))
self.connect(add, thr, sink)
def __init__(self, src, dst, port, pkt_size, sample_rate):
gr.top_block.__init__(self, "dial_tone_source")
amplitude = 0.3
src0 = gr.sig_source_f (sample_rate, gr.GR_SIN_WAVE, 350, amplitude)
src1 = gr.sig_source_f (sample_rate, gr.GR_SIN_WAVE, 440, amplitude)
add = gr.add_ff()
# Throttle needed here to account for the other side's audio card sampling rate
thr = gr.throttle(gr.sizeof_float, sample_rate)
sink = gr.udp_sink(gr.sizeof_float, src, 0, dst, port, pkt_size)
self.connect(src0, (add, 0))
self.connect(src1, (add, 1))
self.connect(add, thr, sink)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, N0, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc_out = trellis.encoder_ss(fo, 0) # initial state = 0
inter = trellis.permutation(interleaver.K(), interleaver.INTER(), 1,
gr.sizeof_short)
enc_in = trellis.encoder_ss(fi, 0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
metrics_in = trellis.metrics_f(
fi.O(), dimensionality, constellation, digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner Viterbi
gnd = gr.vector_source_f([0], True)
siso_in = trellis.siso_f(
fi, K, 0, -1, True, False, trellis.TRELLIS_MIN_SUM
) # Put -1 if the Initial/Final states are not set.
deinter = trellis.permutation(interleaver.K(), interleaver.DEINTER(),
fi.I(), gr.sizeof_float)
va_out = trellis.viterbi_s(
fo, K, 0, -1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc_out, inter, enc_in, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics_in)
tb.connect(gnd, (siso_in, 0))
tb.connect(metrics_in, (siso_in, 1))
tb.connect(siso_in, deinter, va_out, fsmi2s, dst)
tb.run()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def __init__(self, fg, if_rate, af_rate):
self.if_rate = if_rate
self.af_rate = af_rate
self.if_decim = if_rate / af_rate
self.sideband = 1
self.xlate_taps = ([complex(v) for v in file('ssb_taps').readlines()])
self.audio_taps = gr.firdes.low_pass(1.0, self.af_rate, 3e3, 600,
gr.firdes.WIN_HAMMING)
self.xlate = gr.freq_xlating_fir_filter_ccc(self.if_decim,
self.xlate_taps, 0,
self.if_rate)
self.split = gr.complex_to_float()
self.lpf = gr.fir_filter_fff(1, self.audio_taps)
self.sum = gr.add_ff()
self.am_sel = gr.multiply_const_ff(0)
self.sb_sel = gr.multiply_const_ff(1)
self.mixer = gr.add_ff()
self.am_det = gr.complex_to_mag()
fg.connect(self.xlate, self.split)
fg.connect((self.split, 0), (self.sum, 0))
fg.connect((self.split, 1), (self.sum, 1))
fg.connect(self.sum, self.sb_sel)
fg.connect(self.xlate, self.am_det)
fg.connect(self.sb_sel, (self.mixer, 0))
fg.connect(self.am_det, self.am_sel)
fg.connect(self.am_sel, (self.mixer, 1))
fg.connect(self.mixer, self.lpf)
gr.hier_block.__init__(self, fg, self.xlate, self.lpf)
def __init__(self, audio_rate):
gr.hier_block2.__init__(
self,
"standard_squelch",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193, 0, -0.0193),
(1, 1.9524, -0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(
1 / (0.01 * audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193, 0, -0.0193),
(1, 1.3597, -0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1 / (0.01 * audio_rate))
self.sub = gr.sub_ff()
self.add = gr.add_ff()
self.gate = gr.threshold_ff(0.3, 0.43, 0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1 /
(0.01 * audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
self.connect(self, self.input_node)
self.connect(self.input_node, (self.squelch_mult, 0))
self.connect(self.input_node, self.low_iir)
self.connect(self.low_iir, (self.low_square, 0))
self.connect(self.low_iir, (self.low_square, 1))
self.connect(self.low_square, self.low_smooth, (self.sub, 0))
self.connect(self.low_smooth, (self.add, 0))
self.connect(self.input_node, self.hi_iir)
self.connect(self.hi_iir, (self.hi_square, 0))
self.connect(self.hi_iir, (self.hi_square, 1))
self.connect(self.hi_square, self.hi_smooth, (self.sub, 1))
self.connect(self.hi_smooth, (self.add, 1))
self.connect(self.sub, (self.div, 0))
self.connect(self.add, (self.div, 1))
self.connect(self.div, self.gate, self.squelch_lpf,
(self.squelch_mult, 1))
self.connect(self.squelch_mult, self)
def test_031_multiple_internal_inputs(self):
tb = gr.top_block()
src = gr.vector_source_f([1.0])
hb = gr.hier_block2("hb", gr.io_signature(1, 1, gr.sizeof_float), gr.io_signature(1, 1, gr.sizeof_float))
m1 = gr.multiply_const_ff(1.0)
m2 = gr.multiply_const_ff(2.0)
add = gr.add_ff()
hb.connect(hb, m1) # m1 is connected to hb external input #0
hb.connect(hb, m2) # m2 is also connected to hb external input #0
hb.connect(m1, (add, 0))
hb.connect(m2, (add, 1))
hb.connect(add, hb) # add is connected to hb external output #0
dst = gr.vector_sink_f()
tb.connect(src, hb, dst)
tb.run()
self.assertEquals(dst.data(), (3.0,))
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, Es, N0, IT, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the outer FSM input cardinality
#src = gr.vector_source_s([0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1],False)
enc = trellis.pccc_encoder_ss(fo, 0, fi, 0, interleaver, K)
code = gr.vector_sink_s()
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
metrics_in = trellis.metrics_f(
fi.O() * fo.O(), dimensionality, constellation,
digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner SISO
scale = gr.multiply_const_ff(1.0 / N0)
dec = trellis.pccc_decoder_s(fo, 0, -1, fi, 0, -1, interleaver, K, IT,
trellis.TRELLIS_MIN_SUM)
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc, mod)
#tb.connect (src,enc,mod)
#tb.connect(enc,code)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics_in, scale, dec, fsmi2s, dst)
tb.run()
#print code.data()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed,P):
fg = gr.flow_graph ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16*P) # packet size in shorts
s2fsmi=gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the FSM input cardinality
s2p = gr.stream_to_streams(gr.sizeof_short,P) # serial to parallel
enc = trellis.encoder_ss(f,0) # initiali state = 0
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add=[]
noise=[]
for i in range(P):
add.append(gr.add_ff())
noise.append(gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed))
# RX
metrics = trellis.metrics_f(f.O(),dimensionality,constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
va = trellis.viterbi_s(f,K,0,-1) # Put -1 if the Initial/Final states are not set.
p2s = gr.streams_to_stream(gr.sizeof_short,P) # parallel to serial
fsmi2s=gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
fg.connect (src,src_head,s2fsmi,s2p)
for i in range(P):
fg.connect ((s2p,i),(enc,i),(mod,i))
fg.connect ((mod,i),(add[i],0))
fg.connect (noise[i],(add[i],1))
fg.connect (add[i],(metrics,i))
fg.connect ((metrics,i),(va,i),(p2s,i))
fg.connect (p2s,fsmi2s,dst)
fg.run()
# A bit of cheating: run the program once and print the
# final encoder state.
# Then put it as the last argument in the viterbi block
#print "final state = " , enc.ST()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def run_test (f,Kb,bitspersymbol,K,channel,modulation,dimensionality,tot_constellation,N0,seed):
fg = gr.flow_graph ()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0]*(K+2*L)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
for i in range(L): # first/last L symbols set to 0
packet[i] = 0
packet[len(packet)-i-1] = 0
src = gr.vector_source_s(packet,False)
mod = gr.chunks_to_symbols_sf(modulation[1],modulation[0])
# CHANNEL
isi = gr.fir_filter_fff(1,channel)
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
skip = gr.skiphead(gr.sizeof_float, L) # skip the first L samples since you know they are coming from the L zero symbols
#metrics = trellis.metrics_f(f.O(),dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
#va = trellis.viterbi_s(f,K+L,-1,0) # Put -1 if the Initial/Final states are not set.
va = trellis.viterbi_combined_fs(f,K+L,0,0,dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) # using viterbi_combined_fs instead of metrics_f/viterbi_s allows larger packet lengths because metrics_f is complaining for not being able to allocate large buffers. This is due to the large f.O() in this application...
dst = gr.vector_sink_s()
fg.connect (src,mod)
fg.connect (mod,isi,(add,0))
fg.connect (noise,(add,1))
#fg.connect (add,metrics)
#fg.connect (metrics,va,dst)
fg.connect (add,skip,va,dst)
fg.run()
data = dst.data()
ntotal = len(data) - L
nright=0
for i in range(ntotal):
if packet[i+L]==data[i]:
nright=nright+1
#else:
#print "Error in ", i
return (ntotal,ntotal-nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, channel, modulation,
dimensionality, tot_constellation, Es, N0, IT, seed):
tb = gr.top_block()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0] * (K)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
src = gr.vector_source_s(packet, False)
enc_out = trellis.encoder_ss(fo, 0) # initial state = 0
inter = trellis.permutation(interleaver.K(), interleaver.INTER(), 1,
gr.sizeof_short)
mod = gr.chunks_to_symbols_sf(modulation[1], modulation[0])
# CHANNEL
isi = gr.fir_filter_fff(1, channel)
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
(head, tail) = make_rx(tb, fo, fi, dimensionality, tot_constellation, K,
interleaver, IT, Es, N0, trellis.TRELLIS_MIN_SUM)
dst = gr.vector_sink_s()
tb.connect(src, enc_out, inter, mod)
tb.connect(mod, isi, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, head)
tb.connect(tail, dst)
tb.run()
data = dst.data()
ntotal = len(data)
nright = 0
for i in range(ntotal):
if packet[i] == data[i]:
nright = nright + 1
#else:
#print "Error in ", i
return (ntotal, ntotal - nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc_out = trellis.encoder_ss(fo, 0) # initial state = 0
inter = trellis.permutation(interleaver.K(), interleaver.INTER(), 1, gr.sizeof_short)
enc_in = trellis.encoder_ss(fi, 0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
metrics_in = trellis.metrics_f(
fi.O(), dimensionality, constellation, trellis.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner Viterbi
va_in = trellis.viterbi_s(fi, K, 0, -1) # Put -1 if the Initial/Final states are not set.
deinter = trellis.permutation(interleaver.K(), interleaver.DEINTER(), 1, gr.sizeof_short)
metrics_out = trellis.metrics_s(
fo.O(), 1, [0, 1, 2, 3], trellis.TRELLIS_HARD_SYMBOL
) # data preprocessing to generate metrics for outer Viterbi (hard decisions)
va_out = trellis.viterbi_s(fo, K, 0, -1) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc_out, inter, enc_in, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics_in)
tb.connect(metrics_in, va_in, deinter, metrics_out, va_out, fsmi2s, dst)
tb.run()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def __init__(self):
gr.hier_block2.__init__(self,"BER Estimator",
gr.io_signature(1,1,gr.sizeof_float),
gr.io_signature(1,1,gr.sizeof_float))
#TODO Implement a polynomial block in C++ and approximate with polynomials
#of arbitrary order
self.add = gr.add_const_vff((-1, ))
self.square = gr.multiply_ff()
self.mult_lin = gr.multiply_const_ff(-0.20473967)
self.mult_sq = gr.multiply_const_ff(1.5228658)
self.sum = gr.add_ff()
self.connect(self,self.add)
self.connect(self.add,(self.square,0))
self.connect(self.add,(self.square,1))
self.connect(self.square,self.mult_sq,(self.sum,0))
self.connect(self.add,self.mult_lin,(self.sum,1))
self.connect(self.sum,self)
def test_031_multiple_internal_inputs(self):
tb = gr.top_block()
src = gr.vector_source_f([
1.0,
])
hb = gr.hier_block2("hb", gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_float))
m1 = gr.multiply_const_ff(1.0)
m2 = gr.multiply_const_ff(2.0)
add = gr.add_ff()
hb.connect(hb, m1) # m1 is connected to hb external input #0
hb.connect(hb, m2) # m2 is also connected to hb external input #0
hb.connect(m1, (add, 0))
hb.connect(m2, (add, 1))
hb.connect(add, hb) # add is connected to hb external output #0
dst = gr.vector_sink_f()
tb.connect(src, hb, dst)
tb.run()
self.assertEquals(dst.data(), (3.0, ))
def __init__(self):
gr.hier_block2.__init__(self, "BER Estimator",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_float))
#TODO Implement a polynomial block in C++ and approximate with polynomials
#of arbitrary order
self.add = gr.add_const_vff((-1, ))
self.square = gr.multiply_ff()
self.mult_lin = gr.multiply_const_ff(-0.20473967)
self.mult_sq = gr.multiply_const_ff(1.5228658)
self.sum = gr.add_ff()
self.connect(self, self.add)
self.connect(self.add, (self.square, 0))
self.connect(self.add, (self.square, 1))
self.connect(self.square, self.mult_sq, (self.sum, 0))
self.connect(self.add, self.mult_lin, (self.sum, 1))
self.connect(self.sum, self)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,channel,modulation,dimensionality,tot_constellation,Es,N0,IT,seed):
tb = gr.top_block ()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0]*(K)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
src = gr.vector_source_s(packet,False)
enc_out = trellis.encoder_ss(fo,0) # initial state = 0
inter = trellis.permutation(interleaver.K(),interleaver.INTER(),1,gr.sizeof_short)
mod = gr.chunks_to_symbols_sf(modulation[1],modulation[0])
# CHANNEL
isi = gr.fir_filter_fff(1,channel)
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
(head,tail) = make_rx(tb,fo,fi,dimensionality,tot_constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_MIN_SUM)
dst = gr.vector_sink_s();
tb.connect (src,enc_out,inter,mod)
tb.connect (mod,isi,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,head)
tb.connect (tail,dst)
tb.run()
data = dst.data()
ntotal = len(data)
nright=0
for i in range(ntotal):
if packet[i]==data[i]:
nright=nright+1
#else:
#print "Error in ", i
return (ntotal,ntotal-nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, Es, N0, IT, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc = trellis.sccc_encoder_ss(fo, 0, fi, 0, interleaver, K)
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
dec = trellis.sccc_decoder_combined_fs(fo, 0, -1, fi, 0, -1, interleaver,
K, IT, trellis.TRELLIS_MIN_SUM,
dimensionality, constellation,
digital.TRELLIS_EUCLIDEAN, 1.0)
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
#tb.connect (src,src_head,s2fsmi,enc_out,inter,enc_in,mod)
tb.connect(src, src_head, s2fsmi, enc, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
#tb.connect (add,head)
#tb.connect (tail,fsmi2s,dst)
tb.connect(add, dec, fsmi2s, dst)
tb.run()
#print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, Es, N0, IT, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc_out = trellis.encoder_ss(fo, 0) # initial state = 0
inter = trellis.permutation(interleaver.K(), interleaver.INTER(), 1,
gr.sizeof_short)
enc_in = trellis.encoder_ss(fi, 0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
(head, tail) = make_rx(tb, fo, fi, dimensionality, constellation, K,
interleaver, IT, Es, N0, trellis.TRELLIS_MIN_SUM)
#(head,tail) = make_rx(tb,fo,fi,dimensionality,constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_SUM_PRODUCT)
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc_out, inter, enc_in, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, head)
tb.connect(tail, fsmi2s, dst)
tb.run()
#print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def __init__(self, audio_rate):
gr.hier_block2.__init__(self, "standard_squelch",
gr.io_signature(1, 1, gr.sizeof_float), # Input signature
gr.io_signature(1, 1, gr.sizeof_float)) # Output signature
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.9524,-0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.3597,-0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.sub = gr.sub_ff();
self.add = gr.add_ff();
self.gate = gr.threshold_ff(0.3,0.43,0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
self.connect (self, self.input_node)
self.connect (self.input_node, (self.squelch_mult, 0))
self.connect (self.input_node,self.low_iir)
self.connect (self.low_iir,(self.low_square,0))
self.connect (self.low_iir,(self.low_square,1))
self.connect (self.low_square,self.low_smooth,(self.sub,0))
self.connect (self.low_smooth, (self.add,0))
self.connect (self.input_node,self.hi_iir)
self.connect (self.hi_iir,(self.hi_square,0))
self.connect (self.hi_iir,(self.hi_square,1))
self.connect (self.hi_square,self.hi_smooth,(self.sub,1))
self.connect (self.hi_smooth, (self.add,1))
self.connect (self.sub, (self.div, 0))
self.connect (self.add, (self.div, 1))
self.connect (self.div, self.gate, self.squelch_lpf, (self.squelch_mult,1))
self.connect (self.squelch_mult, self)
def __init__(self):
"""
Hierarchical block for FSK demodulation.
The input is the complex modulated signal at baseband
and the output is a stream of floats.
"""
# Initialize base class
gr.hier_block2.__init__(self, "fsk_demod",
gr.io_signature(1, 1, gr.sizeof_gr_complex),
gr.io_signature(1, 1, gr.sizeof_float))
# Variables
self.sps = sps = 2
self.sensitivity = sensitivity = (pi / 2) / sps
self.alpha = alpha = 0.0512 / sps
self.fm_demod = gr.quadrature_demod_cf(1 / sensitivity)
self.freq_offset = gr.single_pole_iir_filter_ff(alpha)
self.sub = gr.sub_ff()
self.add = gr.add_ff()
self.multiply = gr.multiply_ff()
self.invert = gr.multiply_const_vff((-1, ))
# recover the clock
omega = sps
gain_mu = 0.03
mu = 0.5
omega_relative_limit = 0.0002
freq_error = 0.0
gain_omega = .25 * gain_mu * gain_mu # critically damped
self.clock_recovery = digital.clock_recovery_mm_ff(
omega, gain_omega, mu, gain_mu, omega_relative_limit)
self.slice = digital.binary_slicer_fb()
# Connections
self.connect(self.fm_demod, (self.add, 0))
self.connect(self.fm_demod, self.freq_offset, (self.add, 1))
self.connect(self, self.fm_demod)
self.connect(self.add, self.clock_recovery, self.invert, self)
def run_test(f, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the FSM input cardinality
enc = trellis.encoder_ss(f, 0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
va = trellis.viterbi_combined_fs(
f, K, 0, -1, dimensionality, constellation, trellis.TRELLIS_EUCLIDEAN
) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, va, fsmi2s, dst)
tb.run()
# A bit of cheating: run the program once and print the
# final encoder state..
# Then put it as the last argument in the viterbi block
#print "final state = " , enc.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def __init__(self):
"""
Hierarchical block for FSK demodulation.
The input is the complex modulated signal at baseband
and the output is a stream of floats.
"""
# Initialize base class
gr.hier_block2.__init__(
self, "fsk_demod", gr.io_signature(1, 1, gr.sizeof_gr_complex), gr.io_signature(1, 1, gr.sizeof_float)
)
# Variables
self.sps = sps = 2
self.sensitivity = sensitivity = (pi / 2) / sps
self.alpha = alpha = 0.0512 / sps
self.fm_demod = gr.quadrature_demod_cf(1 / sensitivity)
self.freq_offset = gr.single_pole_iir_filter_ff(alpha)
self.sub = gr.sub_ff()
self.add = gr.add_ff()
self.multiply = gr.multiply_ff()
self.invert = gr.multiply_const_vff((-1,))
# recover the clock
omega = sps
gain_mu = 0.03
mu = 0.5
omega_relative_limit = 0.0002
freq_error = 0.0
gain_omega = 0.25 * gain_mu * gain_mu # critically damped
self.clock_recovery = digital.clock_recovery_mm_ff(omega, gain_omega, mu, gain_mu, omega_relative_limit)
self.slice = digital.binary_slicer_fb()
# Connections
self.connect(self.fm_demod, (self.add, 0))
self.connect(self.fm_demod, self.freq_offset, (self.add, 1))
self.connect(self, self.fm_demod)
self.connect(self.add, self.clock_recovery, self.invert, self)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,Es,N0,IT,seed):
tb = gr.top_block ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the outer FSM input cardinality
#src = gr.vector_source_s([0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1],False)
enc = trellis.pccc_encoder_ss(fo,0,fi,0,interleaver,K)
code = gr.vector_sink_s()
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
metrics_in = trellis.metrics_f(fi.O()*fo.O(),dimensionality,constellation,digital.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for innner SISO
scale = gr.multiply_const_ff(1.0/N0)
dec = trellis.pccc_decoder_s(fo,0,-1,fi,0,-1,interleaver,K,IT,trellis.TRELLIS_MIN_SUM)
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect (src,src_head,s2fsmi,enc,mod)
#tb.connect (src,enc,mod)
#tb.connect(enc,code)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics_in,scale,dec,fsmi2s,dst)
tb.run()
#print code.data()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed):
tb = gr.top_block ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the FSM input cardinality
enc = trellis.encoder_ss(f,0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
va = trellis.viterbi_combined_fs(f,K,0,-1,dimensionality,constellation,digital.TRELLIS_EUCLIDEAN) # Put -1 if the Initial/Final states are not set.
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s();
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,va,fsmi2s,dst)
tb.run()
# A bit of cheating: run the program once and print the
# final encoder state..
# Then put it as the last argument in the viterbi block
#print "final state = " , enc.ST()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality, constellation, Es, N0, IT, seed):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(
bitspersymbol, gr.GR_MSB_FIRST
) # unpack shorts to symbols compatible with the outer FSM input cardinality
enc_out = trellis.encoder_ss(fo, 0) # initial state = 0
inter = trellis.permutation(interleaver.K(), interleaver.INTER(), 1, gr.sizeof_short)
enc_in = trellis.encoder_ss(fi, 0) # initial state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
(head, tail) = make_rx(
tb, fo, fi, dimensionality, constellation, K, interleaver, IT, Es, N0, trellis.TRELLIS_MIN_SUM
)
# (head,tail) = make_rx(tb,fo,fi,dimensionality,constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_SUM_PRODUCT)
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc_out, inter, enc_in, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, head)
tb.connect(tail, fsmi2s, dst)
tb.run()
# print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def __init__(self, fg, audio_rate):
self.input_node = gr.add_const_ff(0) # FIXME kludge
self.low_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.9524,-0.9615))
self.low_square = gr.multiply_ff()
self.low_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate)) # 100ms time constant
self.hi_iir = gr.iir_filter_ffd((0.0193,0,-0.0193),(1,1.3597,-0.9615))
self.hi_square = gr.multiply_ff()
self.hi_smooth = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.sub = gr.sub_ff();
self.add = gr.add_ff();
self.gate = gr.threshold_ff(0.3,0.43,0)
self.squelch_lpf = gr.single_pole_iir_filter_ff(1/(0.01*audio_rate))
self.div = gr.divide_ff()
self.squelch_mult = gr.multiply_ff()
fg.connect (self.input_node, (self.squelch_mult, 0))
fg.connect (self.input_node,self.low_iir)
fg.connect (self.low_iir,(self.low_square,0))
fg.connect (self.low_iir,(self.low_square,1))
fg.connect (self.low_square,self.low_smooth,(self.sub,0))
fg.connect (self.low_smooth, (self.add,0))
fg.connect (self.input_node,self.hi_iir)
fg.connect (self.hi_iir,(self.hi_square,0))
fg.connect (self.hi_iir,(self.hi_square,1))
fg.connect (self.hi_square,self.hi_smooth,(self.sub,1))
fg.connect (self.hi_smooth, (self.add,1))
fg.connect (self.sub, (self.div, 0))
fg.connect (self.add, (self.div, 1))
fg.connect (self.div, self.gate, self.squelch_lpf, (self.squelch_mult,1))
gr.hier_block.__init__(self, fg, self.input_node, self.squelch_mult)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,tot_constellation,Es,N0,IT,seed):
fg = gr.flow_graph ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the iouter FSM input cardinality
enc_out = trellis.encoder_ss(fo,0) # initial state = 0
inter = trellis.permutation(interleaver.K(),interleaver.INTER(),1,gr.sizeof_short)
enc_in = trellis.encoder_ss(fi,0) # initial state = 0
# essentially here we implement the combination of modulation and channel as a memoryless modulation (the memory induced by the channel is hidden in the innner FSM)
mod = gr.chunks_to_symbols_sf(tot_constellation,dimensionality)
# CHANNEL
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
(head,tail) = make_rx(fg,fo,fi,dimensionality,tot_constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_MIN_SUM)
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s();
fg.connect (src,src_head,s2fsmi,enc_out,inter,enc_in,mod)
fg.connect (mod,(add,0))
fg.connect (noise,(add,1))
fg.connect (add,head)
fg.connect (tail,fsmi2s,dst)
fg.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#print ntotal,nright,runlength
return (ntotal,ntotal-nright)
def add_ff(N):
op = gr.add_ff()
tb = helper(N, op, gr.sizeof_float, gr.sizeof_float, 2, 1)
return tb
def __init__(self):
gr.top_block.__init__ (self)
parser=OptionParser(option_class=eng_option)
parser.add_option("-H", "--hostname", type="string", default="localhost",
help="set hostname of generic sdr")
parser.add_option("-P", "--portnum", type="int", default=None,
help="set portnum of generic sdr")
parser.add_option("-r", "--sdr_rate", type="eng_float", default=250e3,
help="set sample rate of generic sdr")
parser.add_option("-V", "--volume", type="eng_float", default=None,
help="set volume (default is midpoint)")
parser.add_option("-O", "--audio-output", type="string", default="plughw:0,0",
help="pcm device name (default is plughw:0,0)")
# print help when called with wrong arguments
(options, args) = parser.parse_args()
if len(args) != 0:
parser.print_help()
sys.exit(1)
self.vol = options.volume
if self.vol is None:
self.vol = 0.1
# connect to generic SDR
sdr_rate = options.sdr_rate
audio_decim = 8
audio_rate = int(sdr_rate/audio_decim)
print "audio_rate = ", audio_rate
self.interleaved_short_to_complex = gr.interleaved_short_to_complex()
self.char_to_short = gr.char_to_short(1)
self.sdr_source = grc_blks2.tcp_source(
itemsize=gr.sizeof_char*1,
addr=options.hostname,
port=options.portnum,
server=False
)
# self.sdr_source = gr.file_source(1, 'sdrs_baseband.dat')
# self.throttle = gr.throttle(1, 500e3)
# self.connect(self.sdr_source, self.file_sink)
self.logger = gr.file_sink(1, 'log.out')
self.connect(self.sdr_source, self.logger)
# channel filter
chan_filter_coeffs = gr.firdes.low_pass(
1.0, # gain
sdr_rate, # sampling rate
80e3, # passband cutoff
35e3, # transition width
gr.firdes.WIN_HAMMING)
self.chan_filter = gr.fir_filter_ccf(1, chan_filter_coeffs)
# print "# channel filter:", len(chan_filter_coeffs), "taps"
# PLL-based WFM demod
fm_alpha = 0.25 * 250e3 * math.pi / sdr_rate # 0.767
fm_beta = fm_alpha * fm_alpha / 4.0 # 0.147
fm_max_freq = 2.0 * math.pi * 90e3 / sdr_rate # 2.209
self.fm_demod = gr.pll_freqdet_cf(
1.0, # Loop BW
fm_max_freq, # in radians/sample
-fm_max_freq)
self.fm_demod.set_alpha(fm_alpha)
self.fm_demod.set_beta(fm_beta)
self.connect(self.sdr_source, self.char_to_short)
self.connect(self.char_to_short, self.interleaved_short_to_complex)
self.connect(self.interleaved_short_to_complex, self.chan_filter, self.fm_demod)
# L+R, pilot, L-R, RDS filters
lpr_filter_coeffs = gr.firdes.low_pass(
1.0, # gain
sdr_rate, # sampling rate
15e3, # passband cutoff
1e3, # transition width
gr.firdes.WIN_HAMMING)
self.lpr_filter = gr.fir_filter_fff(audio_decim, lpr_filter_coeffs)
pilot_filter_coeffs = gr.firdes.band_pass(
1.0, # gain
sdr_rate, # sampling rate
19e3-500, # low cutoff
19e3+500, # high cutoff
1e3, # transition width
gr.firdes.WIN_HAMMING)
self.pilot_filter = gr.fir_filter_fff(1, pilot_filter_coeffs)
dsbsc_filter_coeffs = gr.firdes.band_pass(
1.0, # gain
sdr_rate, # sampling rate
38e3-15e3/2, # low cutoff
38e3+15e3/2, # high cutoff
1e3, # transition width
gr.firdes.WIN_HAMMING)
self.dsbsc_filter = gr.fir_filter_fff(1, dsbsc_filter_coeffs)
rds_filter_coeffs = gr.firdes.band_pass(
1.0, # gain
sdr_rate, # sampling rate
57e3-3e3, # low cutoff
57e3+3e3, # high cutoff
3e3, # transition width
gr.firdes.WIN_HAMMING)
self.rds_filter = gr.fir_filter_fff(1, rds_filter_coeffs)
# print "# lpr filter:", len(lpr_filter_coeffs), "taps"
# print "# pilot filter:", len(pilot_filter_coeffs), "taps"
# print "# dsbsc filter:", len(dsbsc_filter_coeffs), "taps"
# print "# rds filter:", len(rds_filter_coeffs), "taps"
self.connect(self.fm_demod, self.lpr_filter)
self.connect(self.fm_demod, self.pilot_filter)
self.connect(self.fm_demod, self.dsbsc_filter)
self.connect(self.fm_demod, self.rds_filter)
# down-convert L-R, RDS
self.stereo_baseband = gr.multiply_ff()
self.connect(self.pilot_filter, (self.stereo_baseband, 0))
self.connect(self.pilot_filter, (self.stereo_baseband, 1))
self.connect(self.dsbsc_filter, (self.stereo_baseband, 2))
self.rds_baseband = gr.multiply_ff()
self.connect(self.pilot_filter, (self.rds_baseband, 0))
self.connect(self.pilot_filter, (self.rds_baseband, 1))
self.connect(self.pilot_filter, (self.rds_baseband, 2))
self.connect(self.rds_filter, (self.rds_baseband, 3))
# low-pass and downsample L-R
lmr_filter_coeffs = gr.firdes.low_pass(
1.0, # gain
sdr_rate, # sampling rate
15e3, # passband cutoff
1e3, # transition width
gr.firdes.WIN_HAMMING)
self.lmr_filter = gr.fir_filter_fff(audio_decim, lmr_filter_coeffs)
self.connect(self.stereo_baseband, self.lmr_filter)
# create L, R from L-R, L+R
self.left = gr.add_ff()
self.right = gr.sub_ff()
self.connect(self.lpr_filter, (self.left, 0))
self.connect(self.lmr_filter, (self.left, 1))
self.connect(self.lpr_filter, (self.right, 0))
self.connect(self.lmr_filter, (self.right, 1))
# volume control, complex2flot, audio sink
self.volume_control_l = gr.multiply_const_ff(self.vol)
self.volume_control_r = gr.multiply_const_ff(self.vol)
output_audio_rate = 48000
self.resamp_L = blks2.rational_resampler_fff(interpolation=output_audio_rate,decimation=audio_rate,taps=None,fractional_bw=None,)
self.resamp_R = blks2.rational_resampler_fff(interpolation=output_audio_rate,decimation=audio_rate,taps=None,fractional_bw=None,)
self.connect(self.left, self.volume_control_l, self.resamp_L)
self.connect(self.right, self.volume_control_r, self.resamp_R)
# self.audio_sink = audio.sink(int(output_audio_rate),
# options.audio_output, False)
# self.connect(self.resamp_L, (self.audio_sink, 0))
# self.connect(self.resamp_R, (self.audio_sink, 1))
self.file_sink1 = gr.file_sink(gr.sizeof_float, 'audioL.dat')
self.file_sink2 = gr.file_sink(gr.sizeof_float, 'audioR.dat')
self.file_sink3 = gr.file_sink(gr.sizeof_float, 'fmDemod.dat')
self.connect(self.resamp_L, self.file_sink1)
self.connect(self.resamp_R, self.file_sink2)
self.connect(self.fm_demod, self.file_sink3)
# low-pass the baseband RDS signal at 1.5kHz
rds_bb_filter_coeffs = gr.firdes.low_pass(
1, # gain
sdr_rate, # sampling rate
1.5e3, # passband cutoff
2e3, # transition width
gr.firdes.WIN_HAMMING)
self.rds_bb_filter = gr.fir_filter_fff(audio_decim, rds_bb_filter_coeffs)
# print "# rds bb filter:", len(rds_bb_filter_coeffs), "taps"
self.connect(self.rds_baseband, self.rds_bb_filter)
# 1187.5bps = 19kHz/16
self.clock_divider = rds.freq_divider(16)
rds_clock_taps = gr.firdes.low_pass(
1, # gain
sdr_rate, # sampling rate
1.2e3, # passband cutoff
1.5e3, # transition width
gr.firdes.WIN_HAMMING)
self.rds_clock = gr.fir_filter_fff(audio_decim, rds_clock_taps)
# print "# rds clock filter:", len(rds_clock_taps), "taps"
self.connect(self.pilot_filter, self.clock_divider, self.rds_clock)
# bpsk_demod, diff_decoder, rds_decoder
self.bpsk_demod = rds.bpsk_demod(audio_rate)
self.differential_decoder = gr.diff_decoder_bb(2)
self.msgq = gr.msg_queue()
self.rds_decoder = rds.data_decoder(self.msgq)
self.connect(self.rds_bb_filter, (self.bpsk_demod, 0))
self.connect(self.rds_clock, (self.bpsk_demod, 1))
self.connect(self.bpsk_demod, self.differential_decoder)
self.connect(self.differential_decoder, self.rds_decoder)
def __init__(self, args, spec, antenna, gain, audio_input):
gr.hier_block2.__init__(self, "transmit_path",
gr.io_signature(0, 0, 0), # Input signature
gr.io_signature(0, 0, 0)) # Output signature
self.u = uhd.usrp_sink(device_addr=args, stream_args=uhd.stream_args('fc32'))
# Set the subdevice spec
if(spec):
self.u.set_subdev_spec(spec, 0)
# Set the antenna
if(antenna):
self.u.set_antenna(antenna, 0)
self.if_rate = 320e3
self.audio_rate = 32e3
self.u.set_samp_rate(self.if_rate)
dev_rate = self.u.get_samp_rate()
self.audio_gain = 10
self.normal_gain = 32000
self.audio = audio.source(int(self.audio_rate), audio_input)
self.audio_amp = gr.multiply_const_ff(self.audio_gain)
lpf = gr.firdes.low_pass (1, # gain
self.audio_rate, # sampling rate
3800, # low pass cutoff freq
300, # width of trans. band
gr.firdes.WIN_HANN) # filter type
hpf = gr.firdes.high_pass (1, # gain
self.audio_rate, # sampling rate
325, # low pass cutoff freq
50, # width of trans. band
gr.firdes.WIN_HANN) # filter type
audio_taps = convolve(array(lpf),array(hpf))
self.audio_filt = gr.fir_filter_fff(1,audio_taps)
self.pl = blks2.ctcss_gen_f(self.audio_rate,123.0)
self.add_pl = gr.add_ff()
self.connect(self.pl,(self.add_pl,1))
self.fmtx = blks2.nbfm_tx(self.audio_rate, self.if_rate)
self.amp = gr.multiply_const_cc (self.normal_gain)
rrate = dev_rate / self.if_rate
self.resamp = blks2.pfb_arb_resampler_ccf(rrate)
self.connect(self.audio, self.audio_amp, self.audio_filt,
(self.add_pl,0), self.fmtx, self.amp,
self.resamp, self.u)
if gain is None:
# if no gain was specified, use the mid-point in dB
g = self.u.get_gain_range()
gain = float(g.start() + g.stop())/2.0
self.set_gain(gain)
self.set_enable(False)
def __init__(self, fft_length, cp_length, snr, kstime, logging):
''' Maximum Likelihood OFDM synchronizer:
J. van de Beek, M. Sandell, and P. O. Borjesson, "ML Estimation
of Time and Frequency Offset in OFDM Systems," IEEE Trans.
Signal Processing, vol. 45, no. 7, pp. 1800-1805, 1997.
'''
gr.hier_block2.__init__(self, "ofdm_sync_ml",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature2(2, 2, gr.sizeof_float, gr.sizeof_char)) # Output signature
self.input = gr.add_const_cc(0)
SNR = 10.0**(snr/10.0)
rho = SNR / (SNR + 1.0)
symbol_length = fft_length + cp_length
# ML Sync
# Energy Detection from ML Sync
self.connect(self, self.input)
# Create a delay line
self.delay = gr.delay(gr.sizeof_gr_complex, fft_length)
self.connect(self.input, self.delay)
# magnitude squared blocks
self.magsqrd1 = gr.complex_to_mag_squared()
self.magsqrd2 = gr.complex_to_mag_squared()
self.adder = gr.add_ff()
moving_sum_taps = [rho/2 for i in range(cp_length)]
self.moving_sum_filter = gr.fir_filter_fff(1,moving_sum_taps)
self.connect(self.input,self.magsqrd1)
self.connect(self.delay,self.magsqrd2)
self.connect(self.magsqrd1,(self.adder,0))
self.connect(self.magsqrd2,(self.adder,1))
self.connect(self.adder,self.moving_sum_filter)
# Correlation from ML Sync
self.conjg = gr.conjugate_cc();
self.mixer = gr.multiply_cc();
movingsum2_taps = [1.0 for i in range(cp_length)]
self.movingsum2 = gr.fir_filter_ccf(1,movingsum2_taps)
# Correlator data handler
self.c2mag = gr.complex_to_mag()
self.angle = gr.complex_to_arg()
self.connect(self.input,(self.mixer,1))
self.connect(self.delay,self.conjg,(self.mixer,0))
self.connect(self.mixer,self.movingsum2,self.c2mag)
self.connect(self.movingsum2,self.angle)
# ML Sync output arg, need to find maximum point of this
self.diff = gr.sub_ff()
self.connect(self.c2mag,(self.diff,0))
self.connect(self.moving_sum_filter,(self.diff,1))
#ML measurements input to sampler block and detect
self.f2c = gr.float_to_complex()
self.pk_detect = gr.peak_detector_fb(0.2, 0.25, 30, 0.0005)
self.sample_and_hold = gr.sample_and_hold_ff()
# use the sync loop values to set the sampler and the NCO
# self.diff = theta
# self.angle = epsilon
self.connect(self.diff, self.pk_detect)
# The DPLL corrects for timing differences between CP correlations
use_dpll = 0
if use_dpll:
self.dpll = gr.dpll_bb(float(symbol_length),0.01)
self.connect(self.pk_detect, self.dpll)
self.connect(self.dpll, (self.sample_and_hold,1))
else:
self.connect(self.pk_detect, (self.sample_and_hold,1))
self.connect(self.angle, (self.sample_and_hold,0))
################################
# correlate against known symbol
# This gives us the same timing signal as the PN sync block only on the preamble
# we don't use the signal generated from the CP correlation because we don't want
# to readjust the timing in the middle of the packet or we ruin the equalizer settings.
kstime = [k.conjugate() for k in kstime]
kstime.reverse()
self.kscorr = gr.fir_filter_ccc(1, kstime)
self.corrmag = gr.complex_to_mag_squared()
self.div = gr.divide_ff()
# The output signature of the correlation has a few spikes because the rest of the
# system uses the repeated preamble symbol. It needs to work that generically if
# anyone wants to use this against a WiMAX-like signal since it, too, repeats.
# The output theta of the correlator above is multiplied with this correlation to
# identify the proper peak and remove other products in this cross-correlation
self.threshold_factor = 0.1
self.slice = gr.threshold_ff(self.threshold_factor, self.threshold_factor, 0)
self.f2b = gr.float_to_char()
self.b2f = gr.char_to_float()
self.mul = gr.multiply_ff()
# Normalize the power of the corr output by the energy. This is not really needed
# and could be removed for performance, but it makes for a cleaner signal.
# if this is removed, the threshold value needs adjustment.
self.connect(self.input, self.kscorr, self.corrmag, (self.div,0))
self.connect(self.moving_sum_filter, (self.div,1))
self.connect(self.div, (self.mul,0))
self.connect(self.pk_detect, self.b2f, (self.mul,1))
self.connect(self.mul, self.slice)
# Set output signals
# Output 0: fine frequency correction value
# Output 1: timing signal
self.connect(self.sample_and_hold, (self,0))
self.connect(self.slice, self.f2b, (self,1))
if logging:
self.connect(self.moving_sum_filter, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-energy_f.dat"))
self.connect(self.diff, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-theta_f.dat"))
self.connect(self.angle, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-epsilon_f.dat"))
self.connect(self.corrmag, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-corrmag_f.dat"))
self.connect(self.kscorr, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-kscorr_c.dat"))
self.connect(self.div, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-div_f.dat"))
self.connect(self.mul, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-mul_f.dat"))
self.connect(self.slice, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-slice_f.dat"))
self.connect(self.pk_detect, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-peaks_b.dat"))
if use_dpll:
self.connect(self.dpll, gr.file_sink(gr.sizeof_char, "ofdm_sync_ml-dpll_b.dat"))
self.connect(self.sample_and_hold, gr.file_sink(gr.sizeof_float, "ofdm_sync_ml-sample_and_hold_f.dat"))
self.connect(self.input, gr.file_sink(gr.sizeof_gr_complex, "ofdm_sync_ml-input_c.dat"))
def __init__(self, demod_rate, audio_decimation):
"""
Hierarchical block for demodulating a broadcast FM signal.
The input is the downconverted complex baseband signal
(gr_complex). The output is two streams of the demodulated
audio (float) 0=Left, 1=Right.
@param demod_rate: input sample rate of complex baseband input.
@type demod_rate: float
@param audio_decimation: how much to decimate demod_rate to get to audio.
@type audio_decimation: integer
"""
gr.hier_block2.__init__(
self,
"wfm_rcv_fmdet",
gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature
gr.io_signature(2, 2, gr.sizeof_float)) # Output signature
lowfreq = -125e3 / demod_rate
highfreq = 125e3 / demod_rate
audio_rate = demod_rate / audio_decimation
# We assign to self so that outsiders can grab the demodulator
# if they need to. E.g., to plot its output.
#
# input: complex; output: float
self.fm_demod = gr.fmdet_cf(demod_rate, lowfreq, highfreq, 0.05)
# input: float; output: float
self.deemph_Left = fm_deemph(audio_rate)
self.deemph_Right = fm_deemph(audio_rate)
# compute FIR filter taps for audio filter
width_of_transition_band = audio_rate / 32
audio_coeffs = gr.firdes.low_pass(
1.0, # gain
demod_rate, # sampling rate
15000,
width_of_transition_band,
gr.firdes.WIN_HAMMING)
# input: float; output: float
self.audio_filter = gr.fir_filter_fff(audio_decimation, audio_coeffs)
if 1:
# Pick off the stereo carrier/2 with this filter. It
# attenuated 10 dB so apply 10 dB gain We pick off the
# negative frequency half because we want to base band by
# it!
## NOTE THIS WAS HACKED TO OFFSET INSERTION LOSS DUE TO
## DEEMPHASIS
stereo_carrier_filter_coeffs = gr.firdes.complex_band_pass(
10.0, demod_rate, -19020, -18980, width_of_transition_band,
gr.firdes.WIN_HAMMING)
#print "len stereo carrier filter = ",len(stereo_carrier_filter_coeffs)
#print "stereo carrier filter ", stereo_carrier_filter_coeffs
#print "width of transition band = ",width_of_transition_band, " audio rate = ", audio_rate
# Pick off the double side band suppressed carrier
# Left-Right audio. It is attenuated 10 dB so apply 10 dB
# gain
stereo_dsbsc_filter_coeffs = gr.firdes.complex_band_pass(
20.0, demod_rate, 38000 - 15000 / 2, 38000 + 15000 / 2,
width_of_transition_band, gr.firdes.WIN_HAMMING)
#print "len stereo dsbsc filter = ",len(stereo_dsbsc_filter_coeffs)
#print "stereo dsbsc filter ", stereo_dsbsc_filter_coeffs
# construct overlap add filter system from coefficients
# for stereo carrier
self.stereo_carrier_filter = gr.fir_filter_fcc(
audio_decimation, stereo_carrier_filter_coeffs)
# carrier is twice the picked off carrier so arrange to do
# a commplex multiply
self.stereo_carrier_generator = gr.multiply_cc()
# Pick off the rds signal
stereo_rds_filter_coeffs = gr.firdes.complex_band_pass(
30.0, demod_rate, 57000 - 1500, 57000 + 1500,
width_of_transition_band, gr.firdes.WIN_HAMMING)
#print "len stereo dsbsc filter = ",len(stereo_dsbsc_filter_coeffs)
#print "stereo dsbsc filter ", stereo_dsbsc_filter_coeffs
# construct overlap add filter system from coefficients for stereo carrier
self.rds_signal_filter = gr.fir_filter_fcc(
audio_decimation, stereo_rds_filter_coeffs)
self.rds_carrier_generator = gr.multiply_cc()
self.rds_signal_generator = gr.multiply_cc()
self_rds_signal_processor = gr.null_sink(gr.sizeof_gr_complex)
loop_bw = 2 * math.pi / 100.0
max_freq = -2.0 * math.pi * 18990 / audio_rate
min_freq = -2.0 * math.pi * 19010 / audio_rate
self.stereo_carrier_pll_recovery = gr.pll_refout_cc(
loop_bw, max_freq, min_freq)
#self.stereo_carrier_pll_recovery.squelch_enable(False)
##pll_refout does not have squelch yet, so disabled for
#now
# set up mixer (multiplier) to get the L-R signal at
# baseband
self.stereo_basebander = gr.multiply_cc()
# pick off the real component of the basebanded L-R
# signal. The imaginary SHOULD be zero
self.LmR_real = gr.complex_to_real()
self.Make_Left = gr.add_ff()
self.Make_Right = gr.sub_ff()
self.stereo_dsbsc_filter = gr.fir_filter_fcc(
audio_decimation, stereo_dsbsc_filter_coeffs)
if 1:
# send the real signal to complex filter to pick off the
# carrier and then to one side of a multiplier
self.connect(self, self.fm_demod, self.stereo_carrier_filter,
self.stereo_carrier_pll_recovery,
(self.stereo_carrier_generator, 0))
# send the already filtered carrier to the otherside of the carrier
# the resulting signal from this multiplier is the carrier
# with correct phase but at -38000 Hz.
self.connect(self.stereo_carrier_pll_recovery,
(self.stereo_carrier_generator, 1))
# send the new carrier to one side of the mixer (multiplier)
self.connect(self.stereo_carrier_generator,
(self.stereo_basebander, 0))
# send the demphasized audio to the DSBSC pick off filter, the complex
# DSBSC signal at +38000 Hz is sent to the other side of the mixer/multiplier
# the result is BASEBANDED DSBSC with phase zero!
self.connect(self.fm_demod, self.stereo_dsbsc_filter,
(self.stereo_basebander, 1))
# Pick off the real part since the imaginary is
# theoretically zero and then to one side of a summer
self.connect(self.stereo_basebander, self.LmR_real,
(self.Make_Left, 0))
#take the same real part of the DSBSC baseband signal and
#send it to negative side of a subtracter
self.connect(self.LmR_real, (self.Make_Right, 1))
# Make rds carrier by taking the squared pilot tone and
# multiplying by pilot tone
self.connect(self.stereo_basebander,
(self.rds_carrier_generator, 0))
self.connect(self.stereo_carrier_pll_recovery,
(self.rds_carrier_generator, 1))
# take signal, filter off rds, send into mixer 0 channel
self.connect(self.fm_demod, self.rds_signal_filter,
(self.rds_signal_generator, 0))
# take rds_carrier_generator output and send into mixer 1
# channel
self.connect(self.rds_carrier_generator,
(self.rds_signal_generator, 1))
# send basebanded rds signal and send into "processor"
# which for now is a null sink
self.connect(self.rds_signal_generator, self_rds_signal_processor)
if 1:
# pick off the audio, L+R that is what we used to have and
# send it to the summer
self.connect(self.fm_demod, self.audio_filter, (self.Make_Left, 1))
# take the picked off L+R audio and send it to the PLUS
# side of the subtractor
self.connect(self.audio_filter, (self.Make_Right, 0))
# The result of Make_Left gets (L+R) + (L-R) and results in 2*L
# The result of Make_Right gets (L+R) - (L-R) and results in 2*R
self.connect(self.Make_Left, self.deemph_Left, (self, 0))
self.connect(self.Make_Right, self.deemph_Right, (self, 1))
def __init__(self, fft_length, block_length, block_header, range, options):
gr.hier_block2.__init__(self, "integer_fo_estimator",
gr.io_signature3(3,3,gr.sizeof_gr_complex,gr.sizeof_float,gr.sizeof_char),
gr.io_signature2(3,3,gr.sizeof_float,gr.sizeof_char))
raise NotImplementedError,"Obsolete class"
self._range = range
# threshold after integer part frequency offset estimation
# if peak value below threshold, assume false triggering
self._thr_lo = 0.4 #0.19 # empirically found threshold. see ioe_metric.float
self._thr_hi = 0.4 #0.2
# stuff to be removed after bugfix for hierblock2s
self.input = gr.kludge_copy(gr.sizeof_gr_complex)
self.time_sync = gr.kludge_copy(gr.sizeof_char)
self.epsilon = (self,1)
self.connect((self,0),self.input)
self.connect((self,2),self.time_sync)
delay(gr.sizeof_char,
block_header.schmidl_fine_sync[0]*block_length)
# sample ofdm symbol (preamble 1 and 2)
sampler_symbol1 = vector_sampler(gr.sizeof_gr_complex,fft_length)
sampler_symbol2 = vector_sampler(gr.sizeof_gr_complex,fft_length)
time_delay1 = delay(gr.sizeof_char,block_length*block_header.schmidl_fine_sync[1])
self.connect(self.input, (sampler_symbol1,0))
self.connect(self.input, (sampler_symbol2,0))
if block_header.schmidl_fine_sync[0] > 0:
time_delay0 = delay(gr.sizeof_char,block_length*block_header.schmidl_fine_sync[0])
self.connect(self.time_sync, time_delay0, (sampler_symbol1,1))
else:
self.connect(self.time_sync, (sampler_symbol1,1))
self.connect(self.time_sync, time_delay1, (sampler_symbol2,1))
# negative fractional frequency offset estimate
epsilon = gr.multiply_const_ff(-1.0)
self.connect(self.epsilon, epsilon)
# compensate for fractional frequency offset on per symbol base
# freq_shift: vector length, modulator sensitivity
# freq_shift third input: reset phase accumulator
# symbol/preamble 1
freq_shift_sym1 = frequency_shift_vcc(fft_length, 1.0/fft_length)
self.connect(sampler_symbol1, (freq_shift_sym1,0))
self.connect(epsilon, (freq_shift_sym1,1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym1,2))
# symbol/preamble 2
freq_shift_sym2 = frequency_shift_vcc(fft_length, 1.0/fft_length)
self.connect(sampler_symbol2, (freq_shift_sym2,0))
self.connect(epsilon, (freq_shift_sym2,1))
self.connect(gr.vector_source_b([1], True), (freq_shift_sym2,2))
# fourier transfrom on both preambles
fft_sym1 = gr.fft_vcc(fft_length, True, [], True) # Forward + Blockshift
fft_sym2 = gr.fft_vcc(fft_length, True, [], True) # Forward + Blockshift
# calculate schmidl's metric for estimation of freq. offset's integer part
assert(hasattr(block_header, "schmidl_fine_sync"))
pre1 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[0]]
pre2 = block_header.pilotsym_fd[block_header.schmidl_fine_sync[1]]
diff_pn = concatenate([[conjugate(math.sqrt(2)*pre2[2*i]/pre1[2*i]),0.0j] for i in arange(len(pre1)/2)])
cfo_estimator = schmidl_cfo_estimator(fft_length, len(pre1),
self._range, diff_pn)
self.connect(freq_shift_sym1, fft_sym1, (cfo_estimator,0)) # preamble 1
self.connect(freq_shift_sym2, fft_sym2, (cfo_estimator,1)) # preamble 2
# search for maximum and its argument in interval [-range .. +range]
#arg_max = arg_max_vff(2*self._range + 1)
arg_max_s = gr.argmax_fs(2*self._range+1)
arg_max = gr.short_to_float()
ifo_max = gr.max_ff(2*self._range + 1) # vlen
ifo_estimate = gr.add_const_ff(-self._range)
self.connect(cfo_estimator, arg_max_s, arg_max, ifo_estimate)
self.connect(cfo_estimator, ifo_max)
self.connect((arg_max_s,1),gr.null_sink(gr.sizeof_short))
# threshold maximal value
ifo_threshold = gr.threshold_ff(self._thr_lo, self._thr_hi, 0.0)
ifo_thr_f2b = gr.float_to_char()
self.connect(ifo_max, ifo_threshold, ifo_thr_f2b)
# gating the streams ifo_estimate (integer part) and epsilon (frac. part)
# if the metric's peak value was above the chosen threshold, assume to have
# found a new burst. peak value below threshold results in blocking the
# streams
self.gate = gate_ff()
self.connect(ifo_thr_f2b, (self.gate,0)) # threshold stream
self.connect(ifo_estimate, (self.gate,1))
self.connect(epsilon, (self.gate,2))
# peak filtering
# resynchronize and suppress peaks that didn't match a preamble
filtered_time_sync = peak_resync_bb(True) # replace
self.connect(self.time_sync, (filtered_time_sync,0))
self.connect(ifo_thr_f2b, (filtered_time_sync,1))
# find complete estimation for frequency offset
# add together fractional and integer part
freq_offset = gr.add_ff()
self.connect((self.gate,1), gr.multiply_const_ff(-1.0), (freq_offset,0)) # integer offset
self.connect((self.gate,2), (freq_offset,1)) # frac offset
# output connections
self.connect(freq_offset, (self,0))
self.connect(filtered_time_sync, (self,1))
self.connect((self.gate,0), (self,2)) # used for frame trigger
#########################################
# debugging
if options.log:
self.epsilon2_sink = gr.vector_sink_f()
self.connect(epsilon, self.epsilon2_sink)
self.connect(cfo_estimator, gr.file_sink(gr.sizeof_float*(self._range*2+1), "data/ioe_metric.float"))
# output joint stream
preamble_stream = gr.streams_to_vector(fft_length * gr.sizeof_gr_complex, 2)
self.connect(fft_sym1, (preamble_stream,0))
self.connect(fft_sym2, (preamble_stream,1))
self.connect(preamble_stream, gr.file_sink(gr.sizeof_gr_complex * 2 * fft_length, "data/preambles.compl"))
# output, preambles before and after correction, magnitude and complex spectrum
self.connect(sampler_symbol1, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length, "data/pre1_bef.compl"))
self.connect(sampler_symbol1, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length, "data/pre1_bef.float"))
self.connect(sampler_symbol2, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length, "data/pre2_bef.compl"))
self.connect(sampler_symbol2, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length, "data/pre2_bef.float"))
self.connect(freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length,"data/pre1.compl"))
self.connect(freq_shift_sym1, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length,"data/pre1.float"))
self.connect(freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True), gr.file_sink(gr.sizeof_gr_complex * fft_length,"data/pre2.compl"))
self.connect(freq_shift_sym2, gr.fft_vcc(fft_length, True, [], True), gr.complex_to_mag(fft_length), gr.file_sink(gr.sizeof_float * fft_length,"data/pre2.float"))
# calculate epsilon from corrected source to check function
test_cp = cyclic_prefixer(fft_length, block_length)
test_eps = foe(fft_length)
self.connect(freq_shift_sym1, test_cp, test_eps, gr.file_sink(gr.sizeof_float, "data/eps_after.float"))
try:
gr.hier_block.update_var_names(self, "ifo_estimator", vars())
gr.hier_block.update_var_names(self, "ifo_estimator", vars(self))
except:
pass
def __init__(self, *args, **kwds):
# begin wxGlade: MyFrame.__init__
kwds["style"] = wx.DEFAULT_FRAME_STYLE
wx.Frame.__init__(self, *args, **kwds)
# Menu Bar
self.frame_1_menubar = wx.MenuBar()
self.SetMenuBar(self.frame_1_menubar)
wxglade_tmp_menu = wx.Menu()
self.Exit = wx.MenuItem(wxglade_tmp_menu, ID_EXIT, "Exit", "Exit", wx.ITEM_NORMAL)
wxglade_tmp_menu.AppendItem(self.Exit)
self.frame_1_menubar.Append(wxglade_tmp_menu, "File")
# Menu Bar end
self.panel_1 = wx.Panel(self, -1)
self.button_1 = wx.Button(self, ID_BUTTON_1, "LSB")
self.button_2 = wx.Button(self, ID_BUTTON_2, "USB")
self.button_3 = wx.Button(self, ID_BUTTON_3, "AM")
self.button_4 = wx.Button(self, ID_BUTTON_4, "CW")
self.button_5 = wx.ToggleButton(self, ID_BUTTON_5, "Upper")
self.slider_1 = wx.Slider(self, ID_SLIDER_1, 0, -15799, 15799, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.button_6 = wx.ToggleButton(self, ID_BUTTON_6, "Lower")
self.slider_2 = wx.Slider(self, ID_SLIDER_2, 0, -15799, 15799, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.panel_5 = wx.Panel(self, -1)
self.label_1 = wx.StaticText(self, -1, " Band\nCenter")
self.text_ctrl_1 = wx.TextCtrl(self, ID_TEXT_1, "")
self.panel_6 = wx.Panel(self, -1)
self.panel_7 = wx.Panel(self, -1)
self.panel_2 = wx.Panel(self, -1)
self.button_7 = wx.ToggleButton(self, ID_BUTTON_7, "Freq")
self.slider_3 = wx.Slider(self, ID_SLIDER_3, 3000, 0, 6000)
self.spin_ctrl_1 = wx.SpinCtrl(self, ID_SPIN_1, "", min=0, max=100)
self.button_8 = wx.ToggleButton(self, ID_BUTTON_8, "Vol")
self.slider_4 = wx.Slider(self, ID_SLIDER_4, 0, 0, 500)
self.slider_5 = wx.Slider(self, ID_SLIDER_5, 0, 0, 20)
self.button_9 = wx.ToggleButton(self, ID_BUTTON_9, "Time")
self.button_11 = wx.Button(self, ID_BUTTON_11, "Rew")
self.button_10 = wx.Button(self, ID_BUTTON_10, "Fwd")
self.panel_3 = wx.Panel(self, -1)
self.label_2 = wx.StaticText(self, -1, "PGA ")
self.panel_4 = wx.Panel(self, -1)
self.panel_8 = wx.Panel(self, -1)
self.panel_9 = wx.Panel(self, -1)
self.label_3 = wx.StaticText(self, -1, "AM Sync\nCarrier")
self.slider_6 = wx.Slider(self, ID_SLIDER_6, 50, 0, 200, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.label_4 = wx.StaticText(self, -1, "Antenna Tune")
self.slider_7 = wx.Slider(self, ID_SLIDER_7, 1575, 950, 2200, style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.panel_10 = wx.Panel(self, -1)
self.button_12 = wx.ToggleButton(self, ID_BUTTON_12, "Auto Tune")
self.button_13 = wx.Button(self, ID_BUTTON_13, "Calibrate")
self.button_14 = wx.Button(self, ID_BUTTON_14, "Reset")
self.panel_11 = wx.Panel(self, -1)
self.panel_12 = wx.Panel(self, -1)
self.__set_properties()
self.__do_layout()
# end wxGlade
parser = OptionParser(option_class=eng_option)
parser.add_option(
"-c", "--ddc-freq", type="eng_float", default=3.9e6, help="set Rx DDC frequency to FREQ", metavar="FREQ"
)
parser.add_option("-a", "--audio_file", default="", help="audio output file", metavar="FILE")
parser.add_option("-r", "--radio_file", default="", help="radio output file", metavar="FILE")
parser.add_option("-i", "--input_file", default="", help="radio input file", metavar="FILE")
parser.add_option("-d", "--decim", type="int", default=250, help="USRP decimation")
parser.add_option(
"-R",
"--rx-subdev-spec",
type="subdev",
default=None,
help="select USRP Rx side A or B (default=first one with a daughterboard)",
)
(options, args) = parser.parse_args()
self.usrp_center = options.ddc_freq
usb_rate = 64e6 / options.decim
self.slider_range = usb_rate * 0.9375
self.f_lo = self.usrp_center - (self.slider_range / 2)
self.f_hi = self.usrp_center + (self.slider_range / 2)
self.af_sample_rate = 32000
fir_decim = long(usb_rate / self.af_sample_rate)
# data point arrays for antenna tuner
self.xdata = []
self.ydata = []
self.tb = gr.top_block()
# radio variables, initial conditions
self.frequency = self.usrp_center
# these map the frequency slider (0-6000) to the actual range
self.f_slider_offset = self.f_lo
self.f_slider_scale = 10000 / options.decim
self.spin_ctrl_1.SetRange(self.f_lo, self.f_hi)
self.text_ctrl_1.SetValue(str(int(self.usrp_center)))
self.slider_5.SetValue(0)
self.AM_mode = False
self.slider_3.SetValue((self.frequency - self.f_slider_offset) / self.f_slider_scale)
self.spin_ctrl_1.SetValue(int(self.frequency))
POWERMATE = True
try:
self.pm = powermate.powermate(self)
except:
sys.stderr.write("Unable to find PowerMate or Contour Shuttle\n")
POWERMATE = False
if POWERMATE:
powermate.EVT_POWERMATE_ROTATE(self, self.on_rotate)
powermate.EVT_POWERMATE_BUTTON(self, self.on_pmButton)
self.active_button = 7
# command line options
if options.audio_file == "":
SAVE_AUDIO_TO_FILE = False
else:
SAVE_AUDIO_TO_FILE = True
if options.radio_file == "":
SAVE_RADIO_TO_FILE = False
else:
SAVE_RADIO_TO_FILE = True
if options.input_file == "":
self.PLAY_FROM_USRP = True
else:
self.PLAY_FROM_USRP = False
if self.PLAY_FROM_USRP:
self.src = usrp.source_s(decim_rate=options.decim)
if options.rx_subdev_spec is None:
options.rx_subdev_spec = pick_subdevice(self.src)
self.src.set_mux(usrp.determine_rx_mux_value(self.src, options.rx_subdev_spec))
self.subdev = usrp.selected_subdev(self.src, options.rx_subdev_spec)
self.src.tune(0, self.subdev, self.usrp_center)
self.tune_offset = 0 # -self.usrp_center - self.src.rx_freq(0)
else:
self.src = gr.file_source(gr.sizeof_short, options.input_file)
self.tune_offset = 2200 # 2200 works for 3.5-4Mhz band
# save radio data to a file
if SAVE_RADIO_TO_FILE:
file = gr.file_sink(gr.sizeof_short, options.radio_file)
self.tb.connect(self.src, file)
# 2nd DDC
xlate_taps = gr.firdes.low_pass(1.0, usb_rate, 16e3, 4e3, gr.firdes.WIN_HAMMING)
self.xlate = gr.freq_xlating_fir_filter_ccf(fir_decim, xlate_taps, self.tune_offset, usb_rate)
# convert rf data in interleaved short int form to complex
s2ss = gr.stream_to_streams(gr.sizeof_short, 2)
s2f1 = gr.short_to_float()
s2f2 = gr.short_to_float()
src_f2c = gr.float_to_complex()
self.tb.connect(self.src, s2ss)
self.tb.connect((s2ss, 0), s2f1)
self.tb.connect((s2ss, 1), s2f2)
self.tb.connect(s2f1, (src_f2c, 0))
self.tb.connect(s2f2, (src_f2c, 1))
# Complex Audio filter
audio_coeffs = gr.firdes.complex_band_pass(
1.0, # gain
self.af_sample_rate, # sample rate
-3000, # low cutoff
0, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING,
) # window
self.slider_1.SetValue(0)
self.slider_2.SetValue(-3000)
self.audio_filter = gr.fir_filter_ccc(1, audio_coeffs)
# Main +/- 16Khz spectrum display
self.fft = fftsink2.fft_sink_c(
self.panel_2, fft_size=512, sample_rate=self.af_sample_rate, average=True, size=(640, 240)
)
# AM Sync carrier
if AM_SYNC_DISPLAY:
self.fft2 = fftsink.fft_sink_c(
self.tb,
self.panel_9,
y_per_div=20,
fft_size=512,
sample_rate=self.af_sample_rate,
average=True,
size=(640, 240),
)
c2f = gr.complex_to_float()
# AM branch
self.sel_am = gr.multiply_const_cc(0)
# the following frequencies turn out to be in radians/sample
# gr.pll_refout_cc(alpha,beta,min_freq,max_freq)
# suggested alpha = X, beta = .25 * X * X
pll = gr.pll_refout_cc(
0.5, 0.0625, (2.0 * math.pi * 7.5e3 / self.af_sample_rate), (2.0 * math.pi * 6.5e3 / self.af_sample_rate)
)
self.pll_carrier_scale = gr.multiply_const_cc(complex(10, 0))
am_det = gr.multiply_cc()
# these are for converting +7.5kHz to -7.5kHz
# for some reason gr.conjugate_cc() adds noise ??
c2f2 = gr.complex_to_float()
c2f3 = gr.complex_to_float()
f2c = gr.float_to_complex()
phaser1 = gr.multiply_const_ff(1)
phaser2 = gr.multiply_const_ff(-1)
# filter for pll generated carrier
pll_carrier_coeffs = gr.firdes.complex_band_pass(
2.0, # gain
self.af_sample_rate, # sample rate
7400, # low cutoff
7600, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING,
) # window
self.pll_carrier_filter = gr.fir_filter_ccc(1, pll_carrier_coeffs)
self.sel_sb = gr.multiply_const_ff(1)
combine = gr.add_ff()
# AGC
sqr1 = gr.multiply_ff()
intr = gr.iir_filter_ffd([0.004, 0], [0, 0.999])
offset = gr.add_const_ff(1)
agc = gr.divide_ff()
self.scale = gr.multiply_const_ff(0.00001)
dst = audio.sink(long(self.af_sample_rate))
self.tb.connect(src_f2c, self.xlate, self.fft)
self.tb.connect(self.xlate, self.audio_filter, self.sel_am, (am_det, 0))
self.tb.connect(self.sel_am, pll, self.pll_carrier_scale, self.pll_carrier_filter, c2f3)
self.tb.connect((c2f3, 0), phaser1, (f2c, 0))
self.tb.connect((c2f3, 1), phaser2, (f2c, 1))
self.tb.connect(f2c, (am_det, 1))
self.tb.connect(am_det, c2f2, (combine, 0))
self.tb.connect(self.audio_filter, c2f, self.sel_sb, (combine, 1))
if AM_SYNC_DISPLAY:
self.tb.connect(self.pll_carrier_filter, self.fft2)
self.tb.connect(combine, self.scale)
self.tb.connect(self.scale, (sqr1, 0))
self.tb.connect(self.scale, (sqr1, 1))
self.tb.connect(sqr1, intr, offset, (agc, 1))
self.tb.connect(self.scale, (agc, 0))
self.tb.connect(agc, dst)
if SAVE_AUDIO_TO_FILE:
f_out = gr.file_sink(gr.sizeof_short, options.audio_file)
sc1 = gr.multiply_const_ff(64000)
f2s1 = gr.float_to_short()
self.tb.connect(agc, sc1, f2s1, f_out)
self.tb.start()
# for mouse position reporting on fft display
em.eventManager.Register(self.Mouse, wx.EVT_MOTION, self.fft.win)
# and left click to re-tune
em.eventManager.Register(self.Click, wx.EVT_LEFT_DOWN, self.fft.win)
# start a timer to check for web commands
if WEB_CONTROL:
self.timer = UpdateTimer(self, 1000) # every 1000 mSec, 1 Sec
wx.EVT_BUTTON(self, ID_BUTTON_1, self.set_lsb)
wx.EVT_BUTTON(self, ID_BUTTON_2, self.set_usb)
wx.EVT_BUTTON(self, ID_BUTTON_3, self.set_am)
wx.EVT_BUTTON(self, ID_BUTTON_4, self.set_cw)
wx.EVT_BUTTON(self, ID_BUTTON_10, self.fwd)
wx.EVT_BUTTON(self, ID_BUTTON_11, self.rew)
wx.EVT_BUTTON(self, ID_BUTTON_13, self.AT_calibrate)
wx.EVT_BUTTON(self, ID_BUTTON_14, self.AT_reset)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_5, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_6, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_7, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_8, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_9, self.on_button)
wx.EVT_SLIDER(self, ID_SLIDER_1, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_2, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_3, self.slide_tune)
wx.EVT_SLIDER(self, ID_SLIDER_4, self.set_volume)
wx.EVT_SLIDER(self, ID_SLIDER_5, self.set_pga)
wx.EVT_SLIDER(self, ID_SLIDER_6, self.am_carrier)
wx.EVT_SLIDER(self, ID_SLIDER_7, self.antenna_tune)
wx.EVT_SPINCTRL(self, ID_SPIN_1, self.spin_tune)
wx.EVT_MENU(self, ID_EXIT, self.TimeToQuit)
def __init__(self, *args, **kwds):
# begin wxGlade: MyFrame.__init__
kwds["style"] = wx.DEFAULT_FRAME_STYLE
wx.Frame.__init__(self, *args, **kwds)
# Menu Bar
self.frame_1_menubar = wx.MenuBar()
self.SetMenuBar(self.frame_1_menubar)
wxglade_tmp_menu = wx.Menu()
self.Exit = wx.MenuItem(wxglade_tmp_menu, ID_EXIT, "Exit", "Exit",
wx.ITEM_NORMAL)
wxglade_tmp_menu.AppendItem(self.Exit)
self.frame_1_menubar.Append(wxglade_tmp_menu, "File")
# Menu Bar end
self.panel_1 = wx.Panel(self, -1)
self.button_1 = wx.Button(self, ID_BUTTON_1, "LSB")
self.button_2 = wx.Button(self, ID_BUTTON_2, "USB")
self.button_3 = wx.Button(self, ID_BUTTON_3, "AM")
self.button_4 = wx.Button(self, ID_BUTTON_4, "CW")
self.button_5 = wx.ToggleButton(self, ID_BUTTON_5, "Upper")
self.slider_fcutoff_hi = wx.Slider(self,
ID_SLIDER_1,
0,
-15798,
15799,
style=wx.SL_HORIZONTAL
| wx.SL_LABELS)
self.button_6 = wx.ToggleButton(self, ID_BUTTON_6, "Lower")
self.slider_fcutoff_lo = wx.Slider(self,
ID_SLIDER_2,
0,
-15799,
15798,
style=wx.SL_HORIZONTAL
| wx.SL_LABELS)
self.panel_5 = wx.Panel(self, -1)
self.label_1 = wx.StaticText(self, -1, " Band\nCenter")
self.text_ctrl_1 = wx.TextCtrl(self, ID_TEXT_1, "")
self.panel_6 = wx.Panel(self, -1)
self.panel_7 = wx.Panel(self, -1)
self.panel_2 = wx.Panel(self, -1)
self.button_7 = wx.ToggleButton(self, ID_BUTTON_7, "Freq")
self.slider_3 = wx.Slider(self, ID_SLIDER_3, 3000, 0, 6000)
self.spin_ctrl_1 = wx.SpinCtrl(self, ID_SPIN_1, "", min=0, max=100)
self.button_8 = wx.ToggleButton(self, ID_BUTTON_8, "Vol")
self.slider_4 = wx.Slider(self, ID_SLIDER_4, 0, 0, 500)
self.slider_5 = wx.Slider(self, ID_SLIDER_5, 0, 0, 20)
self.button_9 = wx.ToggleButton(self, ID_BUTTON_9, "Time")
self.button_11 = wx.Button(self, ID_BUTTON_11, "Rew")
self.button_10 = wx.Button(self, ID_BUTTON_10, "Fwd")
self.panel_3 = wx.Panel(self, -1)
self.label_2 = wx.StaticText(self, -1, "PGA ")
self.panel_4 = wx.Panel(self, -1)
self.panel_8 = wx.Panel(self, -1)
self.panel_9 = wx.Panel(self, -1)
self.label_3 = wx.StaticText(self, -1, "AM Sync\nCarrier")
self.slider_6 = wx.Slider(self,
ID_SLIDER_6,
50,
0,
200,
style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.label_4 = wx.StaticText(self, -1, "Antenna Tune")
self.slider_7 = wx.Slider(self,
ID_SLIDER_7,
1575,
950,
2200,
style=wx.SL_HORIZONTAL | wx.SL_LABELS)
self.panel_10 = wx.Panel(self, -1)
self.button_12 = wx.ToggleButton(self, ID_BUTTON_12, "Auto Tune")
self.button_13 = wx.Button(self, ID_BUTTON_13, "Calibrate")
self.button_14 = wx.Button(self, ID_BUTTON_14, "Reset")
self.panel_11 = wx.Panel(self, -1)
self.panel_12 = wx.Panel(self, -1)
self.__set_properties()
self.__do_layout()
# end wxGlade
parser = OptionParser(option_class=eng_option)
parser.add_option("",
"--address",
type="string",
default="addr=192.168.10.2",
help="Address of UHD device, [default=%default]")
parser.add_option("-c",
"--ddc-freq",
type="eng_float",
default=3.9e6,
help="set Rx DDC frequency to FREQ",
metavar="FREQ")
parser.add_option(
"-s",
"--samp-rate",
type="eng_float",
default=256e3,
help="set sample rate (bandwidth) [default=%default]")
parser.add_option("-a",
"--audio_file",
default="",
help="audio output file",
metavar="FILE")
parser.add_option("-r",
"--radio_file",
default="",
help="radio output file",
metavar="FILE")
parser.add_option("-i",
"--input_file",
default="",
help="radio input file",
metavar="FILE")
parser.add_option(
"-O",
"--audio-output",
type="string",
default="",
help="audio output device name. E.g., hw:0,0, /dev/dsp, or pulse")
(options, args) = parser.parse_args()
self.usrp_center = options.ddc_freq
input_rate = options.samp_rate
self.slider_range = input_rate * 0.9375
self.f_lo = self.usrp_center - (self.slider_range / 2)
self.f_hi = self.usrp_center + (self.slider_range / 2)
self.af_sample_rate = 32000
fir_decim = long(input_rate / self.af_sample_rate)
# data point arrays for antenna tuner
self.xdata = []
self.ydata = []
self.tb = gr.top_block()
# radio variables, initial conditions
self.frequency = self.usrp_center
# these map the frequency slider (0-6000) to the actual range
self.f_slider_offset = self.f_lo
self.f_slider_scale = 10000
self.spin_ctrl_1.SetRange(self.f_lo, self.f_hi)
self.text_ctrl_1.SetValue(str(int(self.usrp_center)))
self.slider_5.SetValue(0)
self.AM_mode = False
self.slider_3.SetValue(
(self.frequency - self.f_slider_offset) / self.f_slider_scale)
self.spin_ctrl_1.SetValue(int(self.frequency))
POWERMATE = True
try:
self.pm = powermate.powermate(self)
except:
sys.stderr.write("Unable to find PowerMate or Contour Shuttle\n")
POWERMATE = False
if POWERMATE:
powermate.EVT_POWERMATE_ROTATE(self, self.on_rotate)
powermate.EVT_POWERMATE_BUTTON(self, self.on_pmButton)
self.active_button = 7
# command line options
if options.audio_file == "": SAVE_AUDIO_TO_FILE = False
else: SAVE_AUDIO_TO_FILE = True
if options.radio_file == "": SAVE_RADIO_TO_FILE = False
else: SAVE_RADIO_TO_FILE = True
if options.input_file == "": self.PLAY_FROM_USRP = True
else: self.PLAY_FROM_USRP = False
if self.PLAY_FROM_USRP:
self.src = uhd.usrp_source(device_addr=options.address,
io_type=uhd.io_type.COMPLEX_FLOAT32,
num_channels=1)
self.src.set_samp_rate(input_rate)
input_rate = self.src.get_samp_rate()
self.src.set_center_freq(self.usrp_center, 0)
self.tune_offset = 0
else:
self.src = gr.file_source(gr.sizeof_short, options.input_file)
self.tune_offset = 2200 # 2200 works for 3.5-4Mhz band
# convert rf data in interleaved short int form to complex
s2ss = gr.stream_to_streams(gr.sizeof_short, 2)
s2f1 = gr.short_to_float()
s2f2 = gr.short_to_float()
src_f2c = gr.float_to_complex()
self.tb.connect(self.src, s2ss)
self.tb.connect((s2ss, 0), s2f1)
self.tb.connect((s2ss, 1), s2f2)
self.tb.connect(s2f1, (src_f2c, 0))
self.tb.connect(s2f2, (src_f2c, 1))
# save radio data to a file
if SAVE_RADIO_TO_FILE:
radio_file = gr.file_sink(gr.sizeof_short, options.radio_file)
self.tb.connect(self.src, radio_file)
# 2nd DDC
xlate_taps = gr.firdes.low_pass ( \
1.0, input_rate, 16e3, 4e3, gr.firdes.WIN_HAMMING )
self.xlate = gr.freq_xlating_fir_filter_ccf ( \
fir_decim, xlate_taps, self.tune_offset, input_rate )
# Complex Audio filter
audio_coeffs = gr.firdes.complex_band_pass(
1.0, # gain
self.af_sample_rate, # sample rate
-3000, # low cutoff
0, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING) # window
self.slider_fcutoff_hi.SetValue(0)
self.slider_fcutoff_lo.SetValue(-3000)
self.audio_filter = gr.fir_filter_ccc(1, audio_coeffs)
# Main +/- 16Khz spectrum display
self.fft = fftsink2.fft_sink_c(self.panel_2,
fft_size=512,
sample_rate=self.af_sample_rate,
average=True,
size=(640, 240))
# AM Sync carrier
if AM_SYNC_DISPLAY:
self.fft2 = fftsink.fft_sink_c(self.tb,
self.panel_9,
y_per_div=20,
fft_size=512,
sample_rate=self.af_sample_rate,
average=True,
size=(640, 240))
c2f = gr.complex_to_float()
# AM branch
self.sel_am = gr.multiply_const_cc(0)
# the following frequencies turn out to be in radians/sample
# gr.pll_refout_cc(alpha,beta,min_freq,max_freq)
# suggested alpha = X, beta = .25 * X * X
pll = gr.pll_refout_cc(.5, .0625,
(2. * math.pi * 7.5e3 / self.af_sample_rate),
(2. * math.pi * 6.5e3 / self.af_sample_rate))
self.pll_carrier_scale = gr.multiply_const_cc(complex(10, 0))
am_det = gr.multiply_cc()
# these are for converting +7.5kHz to -7.5kHz
# for some reason gr.conjugate_cc() adds noise ??
c2f2 = gr.complex_to_float()
c2f3 = gr.complex_to_float()
f2c = gr.float_to_complex()
phaser1 = gr.multiply_const_ff(1)
phaser2 = gr.multiply_const_ff(-1)
# filter for pll generated carrier
pll_carrier_coeffs = gr.firdes.complex_band_pass(
2.0, # gain
self.af_sample_rate, # sample rate
7400, # low cutoff
7600, # high cutoff
100, # transition
gr.firdes.WIN_HAMMING) # window
self.pll_carrier_filter = gr.fir_filter_ccc(1, pll_carrier_coeffs)
self.sel_sb = gr.multiply_const_ff(1)
combine = gr.add_ff()
#AGC
sqr1 = gr.multiply_ff()
intr = gr.iir_filter_ffd([.004, 0], [0, .999])
offset = gr.add_const_ff(1)
agc = gr.divide_ff()
self.scale = gr.multiply_const_ff(0.00001)
dst = audio.sink(long(self.af_sample_rate), options.audio_output)
if self.PLAY_FROM_USRP:
self.tb.connect(self.src, self.xlate, self.fft)
else:
self.tb.connect(src_f2c, self.xlate, self.fft)
self.tb.connect(self.xlate, self.audio_filter, self.sel_am,
(am_det, 0))
self.tb.connect(self.sel_am, pll, self.pll_carrier_scale,
self.pll_carrier_filter, c2f3)
self.tb.connect((c2f3, 0), phaser1, (f2c, 0))
self.tb.connect((c2f3, 1), phaser2, (f2c, 1))
self.tb.connect(f2c, (am_det, 1))
self.tb.connect(am_det, c2f2, (combine, 0))
self.tb.connect(self.audio_filter, c2f, self.sel_sb, (combine, 1))
if AM_SYNC_DISPLAY:
self.tb.connect(self.pll_carrier_filter, self.fft2)
self.tb.connect(combine, self.scale)
self.tb.connect(self.scale, (sqr1, 0))
self.tb.connect(self.scale, (sqr1, 1))
self.tb.connect(sqr1, intr, offset, (agc, 1))
self.tb.connect(self.scale, (agc, 0))
self.tb.connect(agc, dst)
if SAVE_AUDIO_TO_FILE:
f_out = gr.file_sink(gr.sizeof_short, options.audio_file)
sc1 = gr.multiply_const_ff(64000)
f2s1 = gr.float_to_short()
self.tb.connect(agc, sc1, f2s1, f_out)
self.tb.start()
# for mouse position reporting on fft display
self.fft.win.Bind(wx.EVT_LEFT_UP, self.Mouse)
# and left click to re-tune
self.fft.win.Bind(wx.EVT_LEFT_DOWN, self.Click)
# start a timer to check for web commands
if WEB_CONTROL:
self.timer = UpdateTimer(self, 1000) # every 1000 mSec, 1 Sec
wx.EVT_BUTTON(self, ID_BUTTON_1, self.set_lsb)
wx.EVT_BUTTON(self, ID_BUTTON_2, self.set_usb)
wx.EVT_BUTTON(self, ID_BUTTON_3, self.set_am)
wx.EVT_BUTTON(self, ID_BUTTON_4, self.set_cw)
wx.EVT_BUTTON(self, ID_BUTTON_10, self.fwd)
wx.EVT_BUTTON(self, ID_BUTTON_11, self.rew)
wx.EVT_BUTTON(self, ID_BUTTON_13, self.AT_calibrate)
wx.EVT_BUTTON(self, ID_BUTTON_14, self.AT_reset)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_5, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_6, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_7, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_8, self.on_button)
wx.EVT_TOGGLEBUTTON(self, ID_BUTTON_9, self.on_button)
wx.EVT_SLIDER(self, ID_SLIDER_1, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_2, self.set_filter)
wx.EVT_SLIDER(self, ID_SLIDER_3, self.slide_tune)
wx.EVT_SLIDER(self, ID_SLIDER_4, self.set_volume)
wx.EVT_SLIDER(self, ID_SLIDER_5, self.set_pga)
wx.EVT_SLIDER(self, ID_SLIDER_6, self.am_carrier)
wx.EVT_SLIDER(self, ID_SLIDER_7, self.antenna_tune)
wx.EVT_SPINCTRL(self, ID_SPIN_1, self.spin_tune)
wx.EVT_MENU(self, ID_EXIT, self.TimeToQuit)
