/
example_timing.py
230 lines (189 loc) · 8.33 KB
/
example_timing.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
#!/usr/bin/env python
#
# Copyright 2011-2013 Free Software Foundation, Inc.
#
# This file is part of GNU Radio
#
# SPDX-License-Identifier: GPL-3.0-or-later
#
#
from gnuradio import gr, digital, filter
from gnuradio import blocks
from gnuradio import channels
from gnuradio import eng_notation
from gnuradio.eng_arg import eng_float, intx
from argparse import ArgumentParser
import sys
import numpy
try:
from matplotlib import pyplot
except ImportError:
print("Error: could not from matplotlib import pyplot (http://matplotlib.sourceforge.net/)")
sys.exit(1)
class example_timing(gr.top_block):
def __init__(self, N, sps, rolloff, ntaps, bw, noise,
foffset, toffset, poffset, mode=0):
gr.top_block.__init__(self)
rrc_taps = filter.firdes.root_raised_cosine(
sps, sps, 1.0, rolloff, ntaps)
gain = bw
nfilts = 32
rrc_taps_rx = filter.firdes.root_raised_cosine(
nfilts, sps * nfilts, 1.0, rolloff, ntaps * nfilts)
data = 2.0 * numpy.random.randint(0, 2, N) - 1.0
data = numpy.exp(1j * poffset) * data
self.src = blocks.vector_source_c(data.tolist(), False)
self.rrc = filter.interp_fir_filter_ccf(sps, rrc_taps)
self.chn = channels.channel_model(noise, foffset, toffset)
self.off = filter.mmse_resampler_cc(0.20, 1.0)
if mode == 0:
self.clk = digital.pfb_clock_sync_ccf(sps, gain, rrc_taps_rx,
nfilts, nfilts // 2, 1)
self.taps = self.clk.taps()
self.dtaps = self.clk.diff_taps()
self.delay = int(numpy.ceil(((len(rrc_taps) - 1) // 2 +
(len(self.taps[0]) - 1) // 2) // float(sps))) + 1
self.vsnk_err = blocks.vector_sink_f()
self.vsnk_rat = blocks.vector_sink_f()
self.vsnk_phs = blocks.vector_sink_f()
self.connect((self.clk, 1), self.vsnk_err)
self.connect((self.clk, 2), self.vsnk_rat)
self.connect((self.clk, 3), self.vsnk_phs)
else: # mode == 1
mu = 0.5
gain_mu = bw
gain_omega = 0.25 * gain_mu * gain_mu
omega_rel_lim = 0.02
self.clk = digital.clock_recovery_mm_cc(sps, gain_omega,
mu, gain_mu,
omega_rel_lim)
self.vsnk_err = blocks.vector_sink_f()
self.connect((self.clk, 1), self.vsnk_err)
self.vsnk_src = blocks.vector_sink_c()
self.vsnk_clk = blocks.vector_sink_c()
self.connect(self.src, self.rrc, self.chn,
self.off, self.clk, self.vsnk_clk)
self.connect(self.src, self.vsnk_src)
def main():
parser = ArgumentParser(conflict_handler="resolve")
parser.add_argument("-N", "--nsamples", type=int, default=2000,
help="Set the number of samples to process [default=%(default)r]")
parser.add_argument("-S", "--sps", type=int, default=4,
help="Set the samples per symbol [default=%(default)r]")
parser.add_argument("-r", "--rolloff", type=eng_float, default=0.35,
help="Set the rolloff factor [default=%(default)r]")
parser.add_argument("-W", "--bandwidth", type=eng_float, default=2 * numpy.pi / 100.0,
help="Set the loop bandwidth (PFB) or gain (M&M) [default=%(default)r]")
parser.add_argument("-n", "--ntaps", type=int, default=45,
help="Set the number of taps in the filters [default=%(default)r]")
parser.add_argument("--noise", type=eng_float, default=0.0,
help="Set the simulation noise voltage [default=%(default)r]")
parser.add_argument("-f", "--foffset", type=eng_float, default=0.0,
help="Set the simulation's normalized frequency offset (in Hz) [default=%(default)r]")
parser.add_argument("-t", "--toffset", type=eng_float, default=1.0,
help="Set the simulation's timing offset [default=%(default)r]")
parser.add_argument("-p", "--poffset", type=eng_float, default=0.0,
help="Set the simulation's phase offset [default=%(default)r]")
parser.add_argument("-M", "--mode", type=int, default=0,
help="Set the recovery mode (0: polyphase, 1: M&M) [default=%(default)r]")
args = parser.parse_args()
# Adjust N for the interpolation by sps
args.nsamples = args.nsamples // args.sps
# Set up the program-under-test
put = example_timing(args.nsamples, args.sps, args.rolloff,
args.ntaps, args.bandwidth, args.noise,
args.foffset, args.toffset, args.poffset,
args.mode)
put.run()
if args.mode == 0:
data_src = numpy.array(put.vsnk_src.data()[20:])
data_clk = numpy.array(put.vsnk_clk.data()[20:])
data_err = numpy.array(put.vsnk_err.data()[20:])
data_rat = numpy.array(put.vsnk_rat.data()[20:])
data_phs = numpy.array(put.vsnk_phs.data()[20:])
f1 = pyplot.figure(1, figsize=(12, 10), facecolor='w')
# Plot the IQ symbols
s1 = f1.add_subplot(2, 2, 1)
s1.plot(data_src.real, data_src.imag, "bo")
s1.plot(data_clk.real, data_clk.imag, "ro")
s1.set_title("IQ")
s1.set_xlabel("Real part")
s1.set_ylabel("Imag part")
s1.set_xlim([-2, 2])
s1.set_ylim([-2, 2])
# Plot the symbols in time
delay = put.delay
m = len(data_clk.real)
s2 = f1.add_subplot(2, 2, 2)
s2.plot(data_src.real, "bs", markersize=10, label="Input")
s2.plot(data_clk.real[delay:], "ro", label="Recovered")
s2.set_title("Symbols")
s2.set_xlabel("Samples")
s2.set_ylabel("Real Part of Signals")
s2.legend()
# Plot the clock recovery loop's error
s3 = f1.add_subplot(2, 2, 3)
s3.plot(data_err, label="Error")
s3.plot(data_rat, 'r', label="Update rate")
s3.set_title("Clock Recovery Loop Error")
s3.set_xlabel("Samples")
s3.set_ylabel("Error")
s3.set_ylim([-0.5, 0.5])
s3.legend()
# Plot the clock recovery loop's error
s4 = f1.add_subplot(2, 2, 4)
s4.plot(data_phs)
s4.set_title("Clock Recovery Loop Filter Phase")
s4.set_xlabel("Samples")
s4.set_ylabel("Filter Phase")
diff_taps = put.dtaps
ntaps = len(diff_taps[0])
nfilts = len(diff_taps)
t = numpy.arange(0, ntaps * nfilts)
f3 = pyplot.figure(3, figsize=(12, 10), facecolor='w')
s31 = f3.add_subplot(2, 1, 1)
s32 = f3.add_subplot(2, 1, 2)
s31.set_title("Differential Filters")
s32.set_title("FFT of Differential Filters")
for i, d in enumerate(diff_taps):
D = 20.0 * \
numpy.log10(
1e-20 + abs(numpy.fft.fftshift(numpy.fft.fft(d, 10000))))
s31.plot(t[i::nfilts].real, d, "-o")
s32.plot(D)
s32.set_ylim([-120, 10])
# If testing the M&M clock recovery loop
else:
data_src = numpy.array(put.vsnk_src.data()[20:])
data_clk = numpy.array(put.vsnk_clk.data()[20:])
data_err = numpy.array(put.vsnk_err.data()[20:])
f1 = pyplot.figure(1, figsize=(12, 10), facecolor='w')
# Plot the IQ symbols
s1 = f1.add_subplot(2, 2, 1)
s1.plot(data_src.real, data_src.imag, "o")
s1.plot(data_clk.real, data_clk.imag, "ro")
s1.set_title("IQ")
s1.set_xlabel("Real part")
s1.set_ylabel("Imag part")
s1.set_xlim([-2, 2])
s1.set_ylim([-2, 2])
# Plot the symbols in time
s2 = f1.add_subplot(2, 2, 2)
s2.plot(data_src.real, "bs", markersize=10, label="Input")
s2.plot(data_clk.real, "ro", label="Recovered")
s2.set_title("Symbols")
s2.set_xlabel("Samples")
s2.set_ylabel("Real Part of Signals")
s2.legend()
# Plot the clock recovery loop's error
s3 = f1.add_subplot(2, 2, 3)
s3.plot(data_err)
s3.set_title("Clock Recovery Loop Error")
s3.set_xlabel("Samples")
s3.set_ylabel("Error")
pyplot.show()
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
pass