test_tcm.py

这是用python语言写的一个数字广播的信号处理工具包。利用它

#!/usr/bin/env python

from gnuradio import gr
from gnuradio import audio
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,dimensionality,constellation,N0,seed):
    fg = gr.flow_graph ()

    # TX
    src = gr.lfsr_32k_source_s()
    src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
    s2fsmi = gr.packed_to_unpacked_ss(bitspersymbol,gr.GR_MSB_FIRST) # unpack shorts to symbols compatible with the FSM input cardinality
    enc = trellis.encoder_ss(f,0) # initial state = 0
    mod = gr.chunks_to_symbols_sf(constellation,dimensionality)

    # CHANNEL
    add = gr.add_ff()
    noise = gr.noise_source_f(gr.GR_GAUSSIAN,math.sqrt(N0/2),seed)

    # RX
    metrics = trellis.metrics_f(f.O(),dimensionality,constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for Viterbi
    va = trellis.viterbi_s(f,K,0,-1) # Put -1 if the Initial/Final states are not set.
    fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
    dst = gr.check_lfsr_32k_s(); 

    fg.connect (src,src_head,s2fsmi,enc,mod)
    fg.connect (mod,(add,0))
    fg.connect (noise,(add,1))
    fg.connect (add,metrics)
    fg.connect (metrics,va,fsmi2s,dst)
    
    fg.run()
    
    # A bit of cheating: run the program once and print the 
    # final encoder state.
    # Then put it as the last argument in the viterbi block
    #print "final state = " , enc.ST()

    ntotal = dst.ntotal ()
    nright = dst.nright ()
    runlength = dst.runlength ()
    return (ntotal,ntotal-nright)


def main(args):
    nargs = len (args)
    if nargs == 3:
        fname=args[0]
        esn0_db=float(args[1]) # Es/No in dB
        rep=int(args[2]) # number of times the experiment is run to collect enough errors
    else:
        sys.stderr.write ('usage: test_tcm.py fsm_fname Es/No_db  repetitions\n')
        sys.exit (1)

    # system parameters
    f=trellis.fsm(fname) # get the FSM specification from a file
    Kb=1024*16  # packet size in bits (make it multiple of 16 so it can be packed in a short)
    bitspersymbol = int(round(math.log(f.I())/math.log(2))) # bits per FSM input symbol
    K=Kb/bitspersymbol # packet size in trellis steps
    modulation = fsm_utils.psk4 # see fsm_utlis.py for available predefined modulations
    dimensionality = modulation[0]
    constellation = modulation[1] 
    if len(constellation)/dimensionality != f.O():
        sys.stderr.write ('Incompatible FSM output cardinality and modulation size.\n')
        sys.exit (1)
    # calculate average symbol energy
    Es = 0
    for i in range(len(constellation)):
        Es = Es + constellation[i]**2
    Es = Es / (len(constellation)/dimensionality)
    N0=Es/pow(10.0,esn0_db/10.0); # noise variance
    
    tot_s=0
    terr_s=0
    for i in range(rep):
        (s,e)=run_test(f,Kb,bitspersymbol,K,dimensionality,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
        if (i%100==0):
            print i,s,e,tot_s,terr_s, '%e' % ((1.0*terr_s)/tot_s)
    # estimate of the (short) error rate
    print tot_s,terr_s, '%e' % ((1.0*terr_s)/tot_s)


if __name__ == '__main__':
    main (sys.argv[1:])