From 47d6864ea92cf10899d7beebf2cb15eb08c140f2 Mon Sep 17 00:00:00 2001
From: Tom Rondeau <trondeau@vt.edu>
Date: Tue, 28 Feb 2012 16:23:52 -0500
Subject: examples: adding an example of using the channelizer and synthesize
together to reconstruct a signal.
---
gnuradio-examples/python/pfb/CMakeLists.txt | 1 +
gnuradio-examples/python/pfb/Makefile.am | 3 +-
gnuradio-examples/python/pfb/reconstruction.py | 131 +++++++++++++++++++++++++
3 files changed, 134 insertions(+), 1 deletion(-)
create mode 100755 gnuradio-examples/python/pfb/reconstruction.py
(limited to 'gnuradio-examples/python')
diff --git a/gnuradio-examples/python/pfb/CMakeLists.txt b/gnuradio-examples/python/pfb/CMakeLists.txt
index 55dbb16aca..88fdf2eadb 100644
--- a/gnuradio-examples/python/pfb/CMakeLists.txt
+++ b/gnuradio-examples/python/pfb/CMakeLists.txt
@@ -29,6 +29,7 @@ GR_PYTHON_INSTALL(PROGRAMS
resampler.py
synth_filter.py
synth_to_chan.py
+ reconstruction.py
DESTINATION ${GR_PKG_DATA_DIR}/examples/pfb
COMPONENT "gnuradio_examples"
)
diff --git a/gnuradio-examples/python/pfb/Makefile.am b/gnuradio-examples/python/pfb/Makefile.am
index 39c81bfc20..18a024ef52 100644
--- a/gnuradio-examples/python/pfb/Makefile.am
+++ b/gnuradio-examples/python/pfb/Makefile.am
@@ -31,7 +31,8 @@ dist_ourdata_SCRIPTS = \
fmtest.py \
resampler.py \
synth_filter.py \
- synth_to_chan.py
+ synth_to_chan.py \
+ reconstruction.py
dist_ourdata_DATA = \
resampler_demo.grc
diff --git a/gnuradio-examples/python/pfb/reconstruction.py b/gnuradio-examples/python/pfb/reconstruction.py
new file mode 100755
index 0000000000..2b6f9a831a
--- /dev/null
+++ b/gnuradio-examples/python/pfb/reconstruction.py
@@ -0,0 +1,131 @@
+#!/usr/bin/env python
+
+import scipy, math, pylab
+from scipy import fftpack
+from gnuradio import gr, digital, blks2
+
+fftlen = 8192
+
+def main():
+ N = 10000
+ fs = 2000.0
+ Ts = 1.0/fs
+ t = scipy.arange(0, N*Ts, Ts)
+
+ # When playing with the number of channels, be careful about the filter
+ # specs and the channel map of the synthesizer set below.
+ nchans = 10
+
+ # Build the filter(s)
+ bw = 1000
+ tb = 400
+ proto_taps = gr.firdes.low_pass_2(1, nchans*fs, bw, tb, 80,
+ gr.firdes.WIN_BLACKMAN_hARRIS)
+ print "Filter length: ", len(proto_taps)
+
+
+ # Create a modulated signal
+ npwr = 0.01
+ data = scipy.random.randint(0, 256, N)
+ rrc_taps = gr.firdes.root_raised_cosine(1, 2, 1, 0.35, 41)
+
+ src = gr.vector_source_b(data.astype(scipy.uint8).tolist(), False)
+ mod = digital.bpsk_mod(samples_per_symbol=2)
+ chan = gr.channel_model(npwr)
+ rrc = gr.fft_filter_ccc(1, rrc_taps)
+
+ # Split it up into pieces
+ channelizer = blks2.pfb_channelizer_ccf(nchans, proto_taps, 2)
+
+ # Put the pieces back together again
+ syn_taps = [nchans*t for t in proto_taps]
+ synthesizer = gr.pfb_synthesis_filterbank_ccf(nchans, syn_taps, True)
+ src_snk = gr.vector_sink_c()
+ snk = gr.vector_sink_c()
+
+ # Remap the location of the channels
+ # Can be done in synth or channelizer (watch out for rotattions in
+ # the channelizer)
+ synthesizer.set_channel_map([ 0, 1, 2, 3, 4,
+ 15, 16, 17, 18, 19])
+
+ tb = gr.top_block()
+ tb.connect(src, mod, chan, rrc, channelizer)
+ tb.connect(rrc, src_snk)
+
+ vsnk = []
+ for i in xrange(nchans):
+ tb.connect((channelizer,i), (synthesizer, i))
+
+ vsnk.append(gr.vector_sink_c())
+ tb.connect((channelizer,i), vsnk[i])
+
+ tb.connect(synthesizer, snk)
+ tb.run()
+
+ sin = scipy.array(src_snk.data()[1000:])
+ sout = scipy.array(snk.data()[1000:])
+
+
+ # Plot original signal
+ fs_in = nchans*fs
+ f1 = pylab.figure(1, figsize=(16,12), facecolor='w')
+ s11 = f1.add_subplot(2,2,1)
+ s11.psd(sin, NFFT=fftlen, Fs=fs_in)
+ s11.set_title("PSD of Original Signal")
+ s11.set_ylim([-200, -20])
+
+ s12 = f1.add_subplot(2,2,2)
+ s12.plot(sin.real[1000:1500], "o-b")
+ s12.plot(sin.imag[1000:1500], "o-r")
+ s12.set_title("Original Signal in Time")
+
+ start = 1
+ skip = 4
+ s13 = f1.add_subplot(2,2,3)
+ s13.plot(sin.real[start::skip], sin.imag[start::skip], "o")
+ s13.set_title("Constellation")
+ s13.set_xlim([-2, 2])
+ s13.set_ylim([-2, 2])
+
+ # Plot channels
+ nrows = int(scipy.sqrt(nchans))
+ ncols = int(scipy.ceil(float(nchans)/float(nrows)))
+
+ f2 = pylab.figure(2, figsize=(16,12), facecolor='w')
+ for n in xrange(nchans):
+ s = f2.add_subplot(nrows, ncols, n+1)
+ s.psd(vsnk[n].data(), NFFT=fftlen, Fs=fs_in)
+ s.set_title("Channel {0}".format(n))
+ s.set_ylim([-200, -20])
+
+ # Plot reconstructed signal
+ fs_out = 2*nchans*fs
+ f3 = pylab.figure(3, figsize=(16,12), facecolor='w')
+ s31 = f3.add_subplot(2,2,1)
+ s31.psd(sout, NFFT=fftlen, Fs=fs_out)
+ s31.set_title("PSD of Reconstructed Signal")
+ s31.set_ylim([-200, -20])
+
+ s32 = f3.add_subplot(2,2,2)
+ s32.plot(sout.real[1000:1500], "o-b")
+ s32.plot(sout.imag[1000:1500], "o-r")
+ s32.set_title("Reconstructed Signal in Time")
+
+ start = 2
+ skip = 4
+ s33 = f3.add_subplot(2,2,3)
+ s33.plot(sout.real[start::skip], sout.imag[start::skip], "o")
+ s33.set_title("Constellation")
+ s33.set_xlim([-2, 2])
+ s33.set_ylim([-2, 2])
+
+ pylab.show()
+
+
+if __name__ == "__main__":
+ try:
+ main()
+ except KeyboardInterrupt:
+ pass
+
--
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