Several enhancements to gr-trellis and gnuradio-examples/python/channel-coding:

-Added fsm constructor for generating FSM directly from the
generator matrix of binary convolutional codes.
-Added functionality to fsm class to compute the best way to
go from any state to any other state (useful for termination)
-Added soft-in-soft-out (SISO) block for turbo processing
-Added turbo decoding examples



git-svn-id: http://gnuradio.org/svn/gnuradio/trunk@3322 221aa14e-8319-0410-a670-987f0aec2ac5

1 files changed, 139 insertions, 0 deletions

diff --git a/gnuradio-examples/python/channel-coding/test_sccc_turbo.py b/gnuradio-examples/python/channel-coding/test_sccc_turbo.py
new file mode 100755
index 000000000..cdd1ad8b0
--- /dev/null
+++ b/gnuradio-examples/python/channel-coding/test_sccc_turbo.py
@@ -0,0 +1,139 @@
+#!/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 make_rx(fg,fo,fi,dimensionality,constellation,K,interleaver,IT,Es,N0,type):
+    metrics_in = trellis.metrics_f(fi.O(),dimensionality,constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for innner Viterbi
+    scale = gr.multiply_const_ff(1.0/N0)
+    gnd = gr.vector_source_f([0],True);
+
+    inter=[]
+    deinter=[]
+    siso_in=[]
+    siso_out=[]
+
+    for it in range(IT-1):
+      inter.append( trellis.permutation(interleaver.K(),interleaver.INTER(),fi.I(),gr.sizeof_float) )
+      siso_in.append( trellis.siso_f(fi,K,0,3,True,False,type) )
+      deinter.append( trellis.permutation(interleaver.K(),interleaver.DEINTER(),fi.I(),gr.sizeof_float) )
+      siso_out.append( trellis.siso_f(fo,K,0,3,False,True,type) )
+      fg.connect (inter[it],(siso_in[it],0))
+      fg.connect (gnd,(siso_out[it],0))
+      fg.connect (siso_in[it],deinter[it],(siso_out[it],1))
+
+    inter.append( trellis.permutation(interleaver.K(),interleaver.INTER(),fi.I(),gr.sizeof_float) )
+    siso_in.append( trellis.siso_f(fi,K,0,-1,True,False,type) )
+    deinter.append( trellis.permutation(interleaver.K(),interleaver.DEINTER(),fi.I(),gr.sizeof_float) )
+    siso_out.append( trellis.viterbi_s(fo,K,0,-1) )
+    fg.connect (inter[IT-1],(siso_in[IT-1],0))
+    fg.connect (siso_in[IT-1],deinter[IT-1],siso_out[IT-1])
+
+    # connect first stage
+    fg.connect (gnd,inter[0])
+    fg.connect (metrics_in,scale)
+    fg.connect (scale,(siso_in[0],1))
+    for it in range(IT-1):
+      fg.connect (siso_out[it],inter[it+1])
+      fg.connect (metrics_in,(siso_in[it+1],1))
+    return (metrics_in,siso_out[IT-1])
+
+
+def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,Es,N0,IT,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 outer FSM input cardinality
+    enc_out = trellis.encoder_ss(fo,0) # initial state = 0
+    inter = trellis.permutation(interleaver.K(),interleaver.INTER(),1,gr.sizeof_short)
+    enc_in = trellis.encoder_ss(fi,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
+    (head,tail) = make_rx(fg,fo,fi,dimensionality,constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_MIN_SUM)
+    #(head,tail) = make_rx(fg,fo,fi,dimensionality,constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_SUM_PRODUCT)
+    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_out,inter,enc_in,mod)
+    fg.connect (mod,(add,0))
+    fg.connect (noise,(add,1))
+    fg.connect (add,head)
+    fg.connect (tail,fsmi2s,dst)
+
+    fg.run()
+ 
+    #print enc_out.ST(), enc_in.ST()
+    
+    ntotal = dst.ntotal ()
+    nright = dst.nright ()
+    runlength = dst.runlength ()
+    return (ntotal,ntotal-nright)
+
+
+def main(args):
+    nargs = len (args)
+    if nargs == 4:
+        fname_out=args[0]
+        fname_in=args[1]
+        esn0_db=float(args[2]) # Es/No in dB
+        rep=int(args[3]) # number of times the experiment is run to collect enough errors
+    else:
+        sys.stderr.write ('usage: test_tcm.py fsm_name_out fsm_fname_in Es/No_db  repetitions\n')
+        sys.exit (1)
+
+    # system parameters
+    Kb=1024*16  # packet size in bits (make it multiple of 16 so it can be packed in a short)
+    fo=trellis.fsm(fname_out) # get the outer FSM specification from a file
+    fi=trellis.fsm(fname_in) # get the innner FSM specification from a file
+    bitspersymbol = int(round(math.log(fo.I())/math.log(2))) # bits per FSM input symbol
+    if fo.O() != fi.I():
+        sys.stderr.write ('Incompatible cardinality between outer and inner FSM.\n')
+        sys.exit (1)
+    K=Kb/bitspersymbol # packet size in trellis steps
+    interleaver=trellis.interleaver(K,666) # construct a random interleaver
+    modulation = fsm_utils.psk8 # see fsm_utlis.py for available predefined modulations
+    dimensionality = modulation[0]
+    constellation = modulation[1] 
+    if len(constellation)/dimensionality != fi.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); # calculate noise variance
+    IT = 3 # number of turbo iterations
+    
+    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(fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,Es,N0,IT,-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)%10==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 bit) 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:])