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#!/usr/bin/env python
##################################################
# Gnuradio Python Flow Graph
# Title: CPM test
# Author: Achilleas Anastasopoulos
# Description: gnuradio flow graph
# Generated: Thu Feb 19 23:16:23 2009
##################################################
from gnuradio import gr
from gnuradio import trellis, digital
from gnuradio.gr import firdes
from grc_gnuradio import blks2 as grc_blks2
import math
import numpy
import fsm_utils
from gnuradio import trellis
try:
import scipy.stats
except ImportError:
print "Error: Program requires scipy (see: www.scipy.org)."
sys.exit(1)
def run_test(seed,blocksize):
tb = gr.top_block()
##################################################
# Variables
##################################################
M = 2
K = 1
P = 2
h = (1.0*K)/P
L = 3
Q = 4
frac = 0.99
f = trellis.fsm(P,M,L)
# CPFSK signals
#p = numpy.ones(Q)/(2.0)
#q = numpy.cumsum(p)/(1.0*Q)
# GMSK signals
BT=0.3;
tt=numpy.arange(0,L*Q)/(1.0*Q)-L/2.0;
#print tt
p=(0.5*scipy.stats.erfc(2*math.pi*BT*(tt-0.5)/math.sqrt(math.log(2.0))/math.sqrt(2.0))-0.5*scipy.stats.erfc(2*math.pi*BT*(tt+0.5)/math.sqrt(math.log(2.0))/math.sqrt(2.0)))/2.0;
p=p/sum(p)*Q/2.0;
#print p
q=numpy.cumsum(p)/Q;
q=q/q[-1]/2.0;
#print q
(f0T,SS,S,F,Sf,Ff,N) = fsm_utils.make_cpm_signals(K,P,M,L,q,frac)
#print N
#print Ff
Ffa = numpy.insert(Ff,Q,numpy.zeros(N),axis=0)
#print Ffa
MF = numpy.fliplr(numpy.transpose(Ffa))
#print MF
E = numpy.sum(numpy.abs(Sf)**2,axis=0)
Es = numpy.sum(E)/f.O()
#print Es
constellation = numpy.reshape(numpy.transpose(Sf),N*f.O())
#print Ff
#print Sf
#print constellation
#print numpy.max(numpy.abs(SS - numpy.dot(Ff , Sf)))
EsN0_db = 10.0
N0 = Es * 10.0**(-(1.0*EsN0_db)/10.0)
#N0 = 0.0
#print N0
head = 4
tail = 4
numpy.random.seed(seed*666)
data = numpy.random.randint(0, M, head+blocksize+tail+1)
#data = numpy.zeros(blocksize+1+head+tail,'int')
for i in range(head):
data[i]=0
for i in range(tail+1):
data[-i]=0
##################################################
# Blocks
##################################################
random_source_x_0 = gr.vector_source_b(data.tolist(), False)
gr_chunks_to_symbols_xx_0 = gr.chunks_to_symbols_bf((-1, 1), 1)
gr_interp_fir_filter_xxx_0 = gr.interp_fir_filter_fff(Q, p)
gr_frequency_modulator_fc_0 = gr.frequency_modulator_fc(2*math.pi*h*(1.0/Q))
gr_add_vxx_0 = gr.add_vcc(1)
gr_noise_source_x_0 = gr.noise_source_c(gr.GR_GAUSSIAN, (N0/2.0)**0.5, -long(seed))
gr_multiply_vxx_0 = gr.multiply_vcc(1)
gr_sig_source_x_0 = gr.sig_source_c(Q, gr.GR_COS_WAVE, -f0T, 1, 0)
# only works for N=2, do it manually for N>2...
gr_fir_filter_xxx_0_0 = gr.fir_filter_ccc(Q, MF[0].conjugate())
gr_fir_filter_xxx_0_0_0 = gr.fir_filter_ccc(Q, MF[1].conjugate())
gr_streams_to_stream_0 = gr.streams_to_stream(gr.sizeof_gr_complex*1, int(N))
gr_skiphead_0 = gr.skiphead(gr.sizeof_gr_complex*1, int(N*(1+0)))
viterbi = trellis.viterbi_combined_cb(f, head+blocksize+tail, 0, -1, int(N),
constellation, digital.TRELLIS_EUCLIDEAN)
gr_vector_sink_x_0 = gr.vector_sink_b()
##################################################
# Connections
##################################################
tb.connect((random_source_x_0, 0), (gr_chunks_to_symbols_xx_0, 0))
tb.connect((gr_chunks_to_symbols_xx_0, 0), (gr_interp_fir_filter_xxx_0, 0))
tb.connect((gr_interp_fir_filter_xxx_0, 0), (gr_frequency_modulator_fc_0, 0))
tb.connect((gr_frequency_modulator_fc_0, 0), (gr_add_vxx_0, 0))
tb.connect((gr_noise_source_x_0, 0), (gr_add_vxx_0, 1))
tb.connect((gr_add_vxx_0, 0), (gr_multiply_vxx_0, 0))
tb.connect((gr_sig_source_x_0, 0), (gr_multiply_vxx_0, 1))
tb.connect((gr_multiply_vxx_0, 0), (gr_fir_filter_xxx_0_0, 0))
tb.connect((gr_multiply_vxx_0, 0), (gr_fir_filter_xxx_0_0_0, 0))
tb.connect((gr_fir_filter_xxx_0_0, 0), (gr_streams_to_stream_0, 0))
tb.connect((gr_fir_filter_xxx_0_0_0, 0), (gr_streams_to_stream_0, 1))
tb.connect((gr_streams_to_stream_0, 0), (gr_skiphead_0, 0))
tb.connect((gr_skiphead_0, 0), (viterbi, 0))
tb.connect((viterbi, 0), (gr_vector_sink_x_0, 0))
tb.run()
dataest = gr_vector_sink_x_0.data()
#print data
#print numpy.array(dataest)
perr = 0
err = 0
for i in range(blocksize):
if data[head+i] != dataest[head+i]:
#print i
err += 1
if err != 0 :
perr = 1
return (err,perr)
if __name__ == '__main__':
blocksize = 1000
ss=0
ee=0
for i in range(10000):
(s,e) = run_test(i,blocksize)
ss += s
ee += e
if (i+1) % 100 == 0:
print i+1,ss,ee,(1.0*ss)/(i+1)/(1.0*blocksize),(1.0*ee)/(i+1)
print i+1,ss,ee,(1.0*ss)/(i+1)/(1.0*blocksize),(1.0*ee)/(i+1)
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