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#!/usr/bin/env python
from gnuradio import gr
from gnuradio import trellis
from gnuradio import eng_notation
import math
import sys
import random
import fsm_utils
def run_test (f,Kb,bitspersymbol,K,channel,modulation,dimensionality,tot_constellation,N0,seed):
tb = gr.top_block ()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0]*(K+2*L)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
for i in range(L): # first/last L symbols set to 0
packet[i] = 0
packet[len(packet)-i-1] = 0
src = gr.vector_source_s(packet,False)
mod = gr.chunks_to_symbols_sf(modulation[1],modulation[0])
# CHANNEL
isi = gr.fir_filter_fff(1,channel)
add = gr.add_ff()
noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)
# RX
skip = gr.skiphead(gr.sizeof_float, L) # skip the first L samples since you know they are coming from the L zero symbols
#metrics = trellis.metrics_f(f.O(),dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
#va = trellis.viterbi_s(f,K+L,-1,0) # Put -1 if the Initial/Final states are not set.
va = trellis.viterbi_combined_fs(f,K+L,0,0,dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) # using viterbi_combined_fs instead of metrics_f/viterbi_s allows larger packet lengths because metrics_f is complaining for not being able to allocate large buffers. This is due to the large f.O() in this application...
dst = gr.vector_sink_s()
tb.connect (src,mod)
tb.connect (mod,isi,(add,0))
tb.connect (noise,(add,1))
#tb.connect (add,metrics)
#tb.connect (metrics,va,dst)
tb.connect (add,skip,va,dst)
tb.run()
data = dst.data()
ntotal = len(data) - L
nright=0
for i in range(ntotal):
if packet[i+L]==data[i]:
nright=nright+1
#else:
#print "Error in ", i
return (ntotal,ntotal-nright)
def main(args):
nargs = len (args)
if nargs == 2:
esn0_db=float(args[0])
rep=int(args[1])
else:
sys.stderr.write ('usage: test_viterbi_equalization1.py Es/No_db repetitions\n')
sys.exit (1)
# system parameters
Kb=128*16 # packet size in bits (multiple of 16)
modulation = fsm_utils.pam4 # see fsm_utlis.py for available predefined modulations
channel = fsm_utils.c_channel # see fsm_utlis.py for available predefined test channels
f=trellis.fsm(len(modulation[1]),len(channel)) # generate the FSM automatically
bitspersymbol = int(round(math.log(f.I())/math.log(2))) # bits per FSM input symbol
K=Kb/bitspersymbol # packet size in trellis steps
tot_channel = fsm_utils.make_isi_lookup(modulation,channel,True) # generate the lookup table (normalize energy to 1)
dimensionality = tot_channel[0]
tot_constellation = tot_channel[1]
N0=pow(10.0,-esn0_db/10.0); # noise variance
if len(tot_constellation)/dimensionality != f.O():
sys.stderr.write ('Incompatible FSM output cardinality and lookup table size.\n')
sys.exit (1)
tot_s=0 # total number of transmitted shorts
terr_s=0 # total number of shorts in error
terr_p=0 # total number of packets in error
for i in range(rep):
(s,e)=run_test(f,Kb,bitspersymbol,K,channel,modulation,dimensionality,tot_constellation,N0,-long(666+i)) # run experiment with different seed to get different noise realizations
tot_s=tot_s+s
terr_s=terr_s+e
terr_p=terr_p+(terr_s!=0)
if ((i+1)%100==0) : # display progress
print i+1,terr_p, '%.2e' % ((1.0*terr_p)/(i+1)),tot_s,terr_s, '%.2e' % ((1.0*terr_s)/tot_s)
# estimate of the (short or symbol) error rate
print rep,terr_p, '%.2e' % ((1.0*terr_p)/(i+1)),tot_s,terr_s, '%.2e' % ((1.0*terr_s)/tot_s)
if __name__ == '__main__':
main (sys.argv[1:])
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