1#!/usr/bin/env python
2#
3# Copyright 2009,2012,2013 Free Software Foundation, Inc.
4#
5# This file is part of GNU Radio
6#
7# GNU Radio is free software; you can redistribute it and/or modify
8# it under the terms of the GNU General Public License as published by
9# the Free Software Foundation; either version 3, or (at your option)
10# any later version.
11#
12# GNU Radio is distributed in the hope that it will be useful,
13# but WITHOUT ANY WARRANTY; without even the implied warranty of
14# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15# GNU General Public License for more details.
16#
17# You should have received a copy of the GNU General Public License
18# along with GNU Radio; see the file COPYING.  If not, write to
19# the Free Software Foundation, Inc., 51 Franklin Street,
20# Boston, MA 02110-1301, USA.
21#
22
23from __future__ import print_function
24from __future__ import division
25from __future__ import unicode_literals
26from gnuradio import gr
27from gnuradio import blocks
28from gnuradio import filter
29from gnuradio import analog
30from gnuradio import channels
31import sys, math, time
32import numpy
33
34try:
35    import pylab
36except ImportError:
37    print("Error: Program requires matplotlib (see: matplotlib.sourceforge.net).")
38    sys.exit(1)
39
40
41class fmtx(gr.hier_block2):
42    def __init__(self, lo_freq, audio_rate, if_rate):
43
44        gr.hier_block2.__init__(self, "build_fm",
45                                gr.io_signature(1, 1, gr.sizeof_float),
46                                gr.io_signature(1, 1, gr.sizeof_gr_complex))
47
48        fmtx = analog.nbfm_tx(audio_rate, if_rate, max_dev=5e3,
49	                      tau=75e-6, fh=0.925*if_rate/2.0)
50
51        # Local oscillator
52        lo = analog.sig_source_c(if_rate,            # sample rate
53                                 analog.GR_SIN_WAVE, # waveform type
54                                 lo_freq,            # frequency
55                                 1.0,                # amplitude
56                                 0)                  # DC Offset
57        mixer = blocks.multiply_cc()
58
59        self.connect(self, fmtx, (mixer, 0))
60        self.connect(lo, (mixer, 1))
61        self.connect(mixer, self)
62
63class fmtest(gr.top_block):
64    def __init__(self):
65        gr.top_block.__init__(self)
66
67        self._nsamples = 1000000
68        self._audio_rate = 8000
69
70        # Set up N channels with their own baseband and IF frequencies
71        self._N = 5
72        chspacing = 16000
73        freq = [10, 20, 30, 40, 50]
74        f_lo = [0, 1*chspacing, -1*chspacing, 2*chspacing, -2*chspacing]
75
76        self._if_rate = 4*self._N*self._audio_rate
77
78        # Create a signal source and frequency modulate it
79        self.sum = blocks.add_cc()
80        for n in range(self._N):
81            sig = analog.sig_source_f(self._audio_rate, analog.GR_SIN_WAVE, freq[n], 0.5)
82            fm = fmtx(f_lo[n], self._audio_rate, self._if_rate)
83            self.connect(sig, fm)
84            self.connect(fm, (self.sum, n))
85
86        self.head = blocks.head(gr.sizeof_gr_complex, self._nsamples)
87        self.snk_tx = blocks.vector_sink_c()
88        self.channel = channels.channel_model(0.1)
89
90        self.connect(self.sum, self.head, self.channel, self.snk_tx)
91
92
93        # Design the channlizer
94        self._M = 10
95        bw = chspacing / 2.0
96        t_bw = chspacing / 10.0
97        self._chan_rate = self._if_rate / self._M
98        self._taps = filter.firdes.low_pass_2(1, self._if_rate, bw, t_bw,
99                                              attenuation_dB=100,
100                                              window=filter.firdes.WIN_BLACKMAN_hARRIS)
101        tpc = math.ceil(float(len(self._taps)) / float(self._M))
102
103        print("Number of taps:     ", len(self._taps))
104        print("Number of channels: ", self._M)
105        print("Taps per channel:   ", tpc)
106
107        self.pfb = filter.pfb.channelizer_ccf(self._M, self._taps)
108
109        self.connect(self.channel, self.pfb)
110
111        # Create a file sink for each of M output channels of the filter and connect it
112        self.fmdet = list()
113        self.squelch = list()
114        self.snks = list()
115        for i in range(self._M):
116            self.fmdet.append(analog.nbfm_rx(self._audio_rate, self._chan_rate))
117            self.squelch.append(analog.standard_squelch(self._audio_rate*10))
118            self.snks.append(blocks.vector_sink_f())
119            self.connect((self.pfb, i), self.fmdet[i], self.squelch[i], self.snks[i])
120
121    def num_tx_channels(self):
122        return self._N
123
124    def num_rx_channels(self):
125        return self._M
126
127def main():
128
129    fm = fmtest()
130
131    tstart = time.time()
132    fm.run()
133    tend = time.time()
134
135    if 1:
136        fig1 = pylab.figure(1, figsize=(12,10), facecolor="w")
137        fig2 = pylab.figure(2, figsize=(12,10), facecolor="w")
138        fig3 = pylab.figure(3, figsize=(12,10), facecolor="w")
139
140        Ns = 10000
141        Ne = 100000
142
143        fftlen = 8192
144        winfunc = numpy.blackman
145
146        # Plot transmitted signal
147        fs = fm._if_rate
148
149        d = fm.snk_tx.data()[Ns:Ns+Ne]
150        sp1_f = fig1.add_subplot(2, 1, 1)
151
152        X,freq = sp1_f.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs,
153                           window = lambda d: d*winfunc(fftlen),
154                           visible=False)
155        X_in = 10.0*numpy.log10(abs(numpy.fft.fftshift(X)))
156        f_in = numpy.arange(-fs / 2.0, fs / 2.0, fs / float(X_in.size))
157        p1_f = sp1_f.plot(f_in, X_in, "b")
158        sp1_f.set_xlim([min(f_in), max(f_in)+1])
159        sp1_f.set_ylim([-120.0, 20.0])
160
161        sp1_f.set_title("Input Signal", weight="bold")
162        sp1_f.set_xlabel("Frequency (Hz)")
163        sp1_f.set_ylabel("Power (dBW)")
164
165        Ts = 1.0 / fs
166        Tmax = len(d)*Ts
167
168        t_in = numpy.arange(0, Tmax, Ts)
169        x_in = numpy.array(d)
170        sp1_t = fig1.add_subplot(2, 1, 2)
171        p1_t = sp1_t.plot(t_in, x_in.real, "b-o")
172        #p1_t = sp1_t.plot(t_in, x_in.imag, "r-o")
173        sp1_t.set_ylim([-5, 5])
174
175        # Set up the number of rows and columns for plotting the subfigures
176        Ncols = int(numpy.floor(numpy.sqrt(fm.num_rx_channels())))
177        Nrows = int(numpy.floor(fm.num_rx_channels() / Ncols))
178        if(fm.num_rx_channels() % Ncols != 0):
179            Nrows += 1
180
181        # Plot each of the channels outputs. Frequencies on Figure 2 and
182        # time signals on Figure 3
183        fs_o = fm._audio_rate
184        for i in range(len(fm.snks)):
185            # remove issues with the transients at the beginning
186            # also remove some corruption at the end of the stream
187            #    this is a bug, probably due to the corner cases
188            d = fm.snks[i].data()[Ns:Ne]
189
190            sp2_f = fig2.add_subplot(Nrows, Ncols, 1+i)
191            X,freq = sp2_f.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs_o,
192                               window = lambda d: d*winfunc(fftlen),
193                               visible=False)
194            #X_o = 10.0*numpy.log10(abs(numpy.fft.fftshift(X)))
195            X_o = 10.0*numpy.log10(abs(X))
196            #f_o = numpy.arange(-fs_o/2.0, fs_o/2.0, fs_o/float(X_o.size))
197            f_o = numpy.arange(0, fs_o / 2.0, fs_o/2.0/float(X_o.size))
198            p2_f = sp2_f.plot(f_o, X_o, "b")
199            sp2_f.set_xlim([min(f_o), max(f_o)+0.1])
200            sp2_f.set_ylim([-120.0, 20.0])
201            sp2_f.grid(True)
202
203            sp2_f.set_title(("Channel %d" % i), weight="bold")
204            sp2_f.set_xlabel("Frequency (kHz)")
205            sp2_f.set_ylabel("Power (dBW)")
206
207
208            Ts = 1.0 / fs_o
209            Tmax = len(d)*Ts
210            t_o = numpy.arange(0, Tmax, Ts)
211
212            x_t = numpy.array(d)
213            sp2_t = fig3.add_subplot(Nrows, Ncols, 1+i)
214            p2_t = sp2_t.plot(t_o, x_t.real, "b")
215            p2_t = sp2_t.plot(t_o, x_t.imag, "r")
216            sp2_t.set_xlim([min(t_o), max(t_o)+1])
217            sp2_t.set_ylim([-1, 1])
218
219            sp2_t.set_xlabel("Time (s)")
220            sp2_t.set_ylabel("Amplitude")
221
222
223        pylab.show()
224
225
226if __name__ == "__main__":
227    main()
228