def main():
N = 1000000
fs = 8000
freqs = [100, 200, 300, 400, 500]
nchans = 7
sigs = list()
for fi in freqs:
s = gr.sig_source_c(fs, gr.GR_SIN_WAVE, fi, 1)
sigs.append(s)
taps = gr.firdes.low_pass_2(len(freqs), fs, fs / float(nchans) / 2, 100,
100)
print "Num. Taps = %d (taps per filter = %d)" % (len(taps),
len(taps) / nchans)
filtbank = gr.pfb_synthesis_filterbank_ccf(nchans, taps)
head = gr.head(gr.sizeof_gr_complex, N)
snk = gr.vector_sink_c()
tb = gr.top_block()
tb.connect(filtbank, head, snk)
for i, si in enumerate(sigs):
tb.connect(si, (filtbank, i))
tb.run()
if 1:
f1 = pylab.figure(1)
s1 = f1.add_subplot(1, 1, 1)
s1.plot(snk.data()[1000:])
fftlen = 2048
f2 = pylab.figure(2)
s2 = f2.add_subplot(1, 1, 1)
winfunc = scipy.blackman
s2.psd(snk.data()[10000:],
NFFT=fftlen,
Fs=nchans * fs,
noverlap=fftlen / 4,
window=lambda d: d * winfunc(fftlen))
pylab.show()
def main():
N = 1000000
fs = 8000
freqs = [100, 200, 300, 400, 500]
nchans = 7
sigs = list()
for fi in freqs:
s = gr.sig_source_c(fs, gr.GR_SIN_WAVE, fi, 1)
sigs.append(s)
taps = gr.firdes.low_pass_2(len(freqs), fs, fs/float(nchans)/2, 100, 100)
print "Num. Taps = %d (taps per filter = %d)" % (len(taps),
len(taps)/nchans)
filtbank = gr.pfb_synthesis_filterbank_ccf(nchans, taps)
head = gr.head(gr.sizeof_gr_complex, N)
snk = gr.vector_sink_c()
tb = gr.top_block()
tb.connect(filtbank, head, snk)
for i,si in enumerate(sigs):
tb.connect(si, (filtbank, i))
tb.run()
if 1:
f1 = pylab.figure(1)
s1 = f1.add_subplot(1,1,1)
s1.plot(snk.data()[1000:])
fftlen = 2048
f2 = pylab.figure(2)
s2 = f2.add_subplot(1,1,1)
winfunc = scipy.blackman
s2.psd(snk.data()[10000:], NFFT=fftlen,
Fs = nchans*fs,
noverlap=fftlen/4,
window = lambda d: d*winfunc(fftlen))
pylab.show()
def main():
N = 1000000
fs = 8000
freqs = [100, 200, 300, 400, 500]
nchans = 7
sigs = list()
fmtx = list()
for fi in freqs:
s = gr.sig_source_f(fs, gr.GR_SIN_WAVE, fi, 1)
fm = blks2.nbfm_tx (fs, 4*fs, max_dev=10000, tau=75e-6)
sigs.append(s)
fmtx.append(fm)
syntaps = gr.firdes.low_pass_2(len(freqs), fs, fs/float(nchans)/2, 100, 100)
print "Synthesis Num. Taps = %d (taps per filter = %d)" % (len(syntaps),
len(syntaps)/nchans)
chtaps = gr.firdes.low_pass_2(len(freqs), fs, fs/float(nchans)/2, 100, 100)
print "Channelizer Num. Taps = %d (taps per filter = %d)" % (len(chtaps),
len(chtaps)/nchans)
filtbank = gr.pfb_synthesis_filterbank_ccf(nchans, syntaps)
channelizer = blks2.pfb_channelizer_ccf(nchans, chtaps)
noise_level = 0.01
head = gr.head(gr.sizeof_gr_complex, N)
noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_level)
addnoise = gr.add_cc()
snk_synth = gr.vector_sink_c()
tb = gr.top_block()
tb.connect(noise, (addnoise,0))
tb.connect(filtbank, head, (addnoise, 1))
tb.connect(addnoise, channelizer)
tb.connect(addnoise, snk_synth)
snk = list()
for i,si in enumerate(sigs):
tb.connect(si, fmtx[i], (filtbank, i))
for i in xrange(nchans):
snk.append(gr.vector_sink_c())
tb.connect((channelizer, i), snk[i])
tb.run()
if 1:
channel = 1
data = snk[channel].data()[1000:]
f1 = pylab.figure(1)
s1 = f1.add_subplot(1,1,1)
s1.plot(data[10000:10200] )
s1.set_title(("Output Signal from Channel %d" % channel))
fftlen = 2048
winfunc = scipy.blackman
#winfunc = scipy.hamming
f2 = pylab.figure(2)
s2 = f2.add_subplot(1,1,1)
s2.psd(data, NFFT=fftlen,
Fs = nchans*fs,
noverlap=fftlen/4,
window = lambda d: d*winfunc(fftlen))
s2.set_title(("Output PSD from Channel %d" % channel))
f3 = pylab.figure(3)
s3 = f3.add_subplot(1,1,1)
s3.psd(snk_synth.data()[1000:], NFFT=fftlen,
Fs = nchans*fs,
noverlap=fftlen/4,
window = lambda d: d*winfunc(fftlen))
s3.set_title("Output of Synthesis Filter")
pylab.show()
def main():
N = 1000000
fs = 8000
freqs = [100, 200, 300, 400, 500]
nchans = 7
sigs = list()
fmtx = list()
for fi in freqs:
s = gr.sig_source_f(fs, gr.GR_SIN_WAVE, fi, 1)
fm = blks2.nbfm_tx(fs, 4 * fs, max_dev=10000, tau=75e-6)
sigs.append(s)
fmtx.append(fm)
syntaps = gr.firdes.low_pass_2(len(freqs), fs, fs / float(nchans) / 2, 100,
100)
print "Synthesis Num. Taps = %d (taps per filter = %d)" % (
len(syntaps), len(syntaps) / nchans)
chtaps = gr.firdes.low_pass_2(len(freqs), fs, fs / float(nchans) / 2, 100,
100)
print "Channelizer Num. Taps = %d (taps per filter = %d)" % (
len(chtaps), len(chtaps) / nchans)
filtbank = gr.pfb_synthesis_filterbank_ccf(nchans, syntaps)
channelizer = blks2.pfb_channelizer_ccf(nchans, chtaps)
noise_level = 0.01
head = gr.head(gr.sizeof_gr_complex, N)
noise = gr.noise_source_c(gr.GR_GAUSSIAN, noise_level)
addnoise = gr.add_cc()
snk_synth = gr.vector_sink_c()
tb = gr.top_block()
tb.connect(noise, (addnoise, 0))
tb.connect(filtbank, head, (addnoise, 1))
tb.connect(addnoise, channelizer)
tb.connect(addnoise, snk_synth)
snk = list()
for i, si in enumerate(sigs):
tb.connect(si, fmtx[i], (filtbank, i))
for i in xrange(nchans):
snk.append(gr.vector_sink_c())
tb.connect((channelizer, i), snk[i])
tb.run()
if 1:
channel = 1
data = snk[channel].data()[1000:]
f1 = pylab.figure(1)
s1 = f1.add_subplot(1, 1, 1)
s1.plot(data[10000:10200])
s1.set_title(("Output Signal from Channel %d" % channel))
fftlen = 2048
winfunc = scipy.blackman
#winfunc = scipy.hamming
f2 = pylab.figure(2)
s2 = f2.add_subplot(1, 1, 1)
s2.psd(data,
NFFT=fftlen,
Fs=nchans * fs,
noverlap=fftlen / 4,
window=lambda d: d * winfunc(fftlen))
s2.set_title(("Output PSD from Channel %d" % channel))
f3 = pylab.figure(3)
s3 = f3.add_subplot(1, 1, 1)
s3.psd(snk_synth.data()[1000:],
NFFT=fftlen,
Fs=nchans * fs,
noverlap=fftlen / 4,
window=lambda d: d * winfunc(fftlen))
s3.set_title("Output of Synthesis Filter")
pylab.show()
