--- /dev/null
+#!/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
+from gnuradio.gr import firdes
+from grc_gnuradio import blks2 as grc_blks2
+import math
+import numpy
+import scipy.stats
+import fsm_utils
+from gnuradio import trellis
+
+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, 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, N)
+ gr_skiphead_0 = gr.skiphead(gr.sizeof_gr_complex*1, N*(1+0))
+ viterbi = trellis.viterbi_combined_cb(f, head+blocksize+tail, 0, -1, N, constellation, trellis.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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