#!/usr/bin/env python
#
# Copyright 2009,2012,2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# SPDX-License-Identifier: GPL-3.0-or-later
#
#
from gnuradio import gr
from gnuradio import blocks
from gnuradio import filter
from gnuradio.fft import window
from gnuradio import analog
from gnuradio import channels
import sys
import math
import time
import numpy
try:
import pylab
except ImportError:
print("Error: Program requires matplotlib (see: matplotlib.sourceforge.net).")
sys.exit(1)
class fmtx(gr.hier_block2):
def __init__(self, lo_freq, audio_rate, if_rate):
gr.hier_block2.__init__(self, "build_fm",
gr.io_signature(1, 1, gr.sizeof_float),
gr.io_signature(1, 1, gr.sizeof_gr_complex))
fmtx = analog.nbfm_tx(audio_rate, if_rate, max_dev=5e3,
tau=75e-6, fh=0.925 * if_rate / 2.0)
# Local oscillator
lo = analog.sig_source_c(if_rate, # sample rate
analog.GR_SIN_WAVE, # waveform type
lo_freq, # frequency
1.0, # amplitude
0) # DC Offset
mixer = blocks.multiply_cc()
self.connect(self, fmtx, (mixer, 0))
self.connect(lo, (mixer, 1))
self.connect(mixer, self)
class fmtest(gr.top_block):
def __init__(self):
gr.top_block.__init__(self)
self._nsamples = 1000000
self._audio_rate = 8000
# Set up N channels with their own baseband and IF frequencies
self._N = 5
chspacing = 16000
freq = [10, 20, 30, 40, 50]
f_lo = [0, 1 * chspacing, -1 * chspacing,
2 * chspacing, -2 * chspacing]
self._if_rate = 4 * self._N * self._audio_rate
# Create a signal source and frequency modulate it
self.sum = blocks.add_cc()
for n in range(self._N):
sig = analog.sig_source_f(
self._audio_rate, analog.GR_SIN_WAVE, freq[n], 0.5)
fm = fmtx(f_lo[n], self._audio_rate, self._if_rate)
self.connect(sig, fm)
self.connect(fm, (self.sum, n))
self.head = blocks.head(gr.sizeof_gr_complex, self._nsamples)
self.snk_tx = blocks.vector_sink_c()
self.channel = channels.channel_model(0.1)
self.connect(self.sum, self.head, self.channel, self.snk_tx)
# Design the channlizer
self._M = 10
bw = chspacing / 2.0
t_bw = chspacing / 10.0
self._chan_rate = self._if_rate / self._M
self._taps = filter.firdes.low_pass_2(1, self._if_rate, bw, t_bw,
attenuation_dB=100,
window=window.WIN_BLACKMAN_hARRIS)
tpc = math.ceil(float(len(self._taps)) / float(self._M))
print("Number of taps: ", len(self._taps))
print("Number of channels: ", self._M)
print("Taps per channel: ", tpc)
self.pfb = filter.pfb.channelizer_ccf(self._M, self._taps)
self.connect(self.channel, self.pfb)
# Create a file sink for each of M output channels of the filter and connect it
self.fmdet = list()
self.squelch = list()
self.snks = list()
for i in range(self._M):
self.fmdet.append(analog.nbfm_rx(
self._audio_rate, self._chan_rate))
self.squelch.append(analog.standard_squelch(self._audio_rate * 10))
self.snks.append(blocks.vector_sink_f())
self.connect(
(self.pfb, i), self.fmdet[i], self.squelch[i], self.snks[i])
def num_tx_channels(self):
return self._N
def num_rx_channels(self):
return self._M
def main():
fm = fmtest()
tstart = time.time()
fm.run()
tend = time.time()
if 1:
fig1 = pylab.figure(1, figsize=(12, 10), facecolor="w")
fig2 = pylab.figure(2, figsize=(12, 10), facecolor="w")
fig3 = pylab.figure(3, figsize=(12, 10), facecolor="w")
Ns = 10000
Ne = 100000
fftlen = 8192
winfunc = numpy.blackman
# Plot transmitted signal
fs = fm._if_rate
d = fm.snk_tx.data()[Ns:Ns + Ne]
sp1_f = fig1.add_subplot(2, 1, 1)
X, freq = sp1_f.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs,
window=lambda d: d * winfunc(fftlen),
visible=False)
X_in = 10.0 * numpy.log10(abs(numpy.fft.fftshift(X)))
f_in = numpy.arange(-fs / 2.0, fs / 2.0, fs / float(X_in.size))
p1_f = sp1_f.plot(f_in, X_in, "b")
sp1_f.set_xlim([min(f_in), max(f_in) + 1])
sp1_f.set_ylim([-120.0, 20.0])
sp1_f.set_title("Input Signal", weight="bold")
sp1_f.set_xlabel("Frequency (Hz)")
sp1_f.set_ylabel("Power (dBW)")
Ts = 1.0 / fs
Tmax = len(d) * Ts
t_in = numpy.arange(0, Tmax, Ts)
x_in = numpy.array(d)
sp1_t = fig1.add_subplot(2, 1, 2)
p1_t = sp1_t.plot(t_in, x_in.real, "b-o")
#p1_t = sp1_t.plot(t_in, x_in.imag, "r-o")
sp1_t.set_ylim([-5, 5])
# Set up the number of rows and columns for plotting the subfigures
Ncols = int(numpy.floor(numpy.sqrt(fm.num_rx_channels())))
Nrows = int(numpy.floor(fm.num_rx_channels() / Ncols))
if(fm.num_rx_channels() % Ncols != 0):
Nrows += 1
# Plot each of the channels outputs. Frequencies on Figure 2 and
# time signals on Figure 3
fs_o = fm._audio_rate
for i in range(len(fm.snks)):
# remove issues with the transients at the beginning
# also remove some corruption at the end of the stream
# this is a bug, probably due to the corner cases
d = fm.snks[i].data()[Ns:Ne]
sp2_f = fig2.add_subplot(Nrows, Ncols, 1 + i)
X, freq = sp2_f.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs_o,
window=lambda d: d * winfunc(fftlen),
visible=False)
#X_o = 10.0*numpy.log10(abs(numpy.fft.fftshift(X)))
X_o = 10.0 * numpy.log10(abs(X))
#f_o = numpy.arange(-fs_o/2.0, fs_o/2.0, fs_o/float(X_o.size))
f_o = numpy.arange(0, fs_o / 2.0, fs_o / 2.0 / float(X_o.size))
p2_f = sp2_f.plot(f_o, X_o, "b")
sp2_f.set_xlim([min(f_o), max(f_o) + 0.1])
sp2_f.set_ylim([-120.0, 20.0])
sp2_f.grid(True)
sp2_f.set_title(("Channel %d" % i), weight="bold")
sp2_f.set_xlabel("Frequency (kHz)")
sp2_f.set_ylabel("Power (dBW)")
Ts = 1.0 / fs_o
Tmax = len(d) * Ts
t_o = numpy.arange(0, Tmax, Ts)
x_t = numpy.array(d)
sp2_t = fig3.add_subplot(Nrows, Ncols, 1 + i)
p2_t = sp2_t.plot(t_o, x_t.real, "b")
p2_t = sp2_t.plot(t_o, x_t.imag, "r")
sp2_t.set_xlim([min(t_o), max(t_o) + 1])
sp2_t.set_ylim([-1, 1])
sp2_t.set_xlabel("Time (s)")
sp2_t.set_ylabel("Amplitude")
pylab.show()
if __name__ == "__main__":
main()