def make_rx(tb, fo, fi, dimensionality, tot_constellation, K, interleaver, IT,
Es, N0, type):
metrics_in = trellis.metrics_f(
fi.O(), dimensionality, tot_constellation, digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner SISO
scale = gr.multiply_const_ff(1.0 / N0)
gnd = gr.vector_source_f([0], True)
inter = []
deinter = []
siso_in = []
siso_out = []
# generate all blocks
for it in range(IT):
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))
if it < IT - 1:
siso_out.append(trellis.siso_f(fo, K, 0, -1, False, True, type))
else:
siso_out.append(trellis.viterbi_s(fo, K, 0,
-1)) # no soft outputs needed
# connect first stage
tb.connect(gnd, inter[0])
tb.connect(metrics_in, scale)
tb.connect(scale, (siso_in[0], 1))
# connect the rest
for it in range(IT):
if it < IT - 1:
tb.connect(scale, (siso_in[it + 1], 1))
tb.connect(siso_in[it], deinter[it], (siso_out[it], 1))
tb.connect(gnd, (siso_out[it], 0))
tb.connect(siso_out[it], inter[it + 1])
tb.connect(inter[it], (siso_in[it], 0))
else:
tb.connect(siso_in[it], deinter[it], siso_out[it])
tb.connect(inter[it], (siso_in[it], 0))
return (metrics_in, siso_out[IT - 1])
def make_rx(tb, fo, fi, dimensionality, tot_constellation, K, interleaver, IT, Es, N0, type):
metrics_in = trellis.metrics_f(
fi.O(), dimensionality, tot_constellation, digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner SISO
scale = blocks.multiply_const_ff(1.0 / N0)
gnd = blocks.vector_source_f([0], True)
inter = []
deinter = []
siso_in = []
siso_out = []
# generate all blocks
for it in range(IT):
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))
if it < IT - 1:
siso_out.append(trellis.siso_f(fo, K, 0, -1, False, True, type))
else:
siso_out.append(trellis.viterbi_s(fo, K, 0, -1)) # no soft outputs needed
# connect first stage
tb.connect(gnd, inter[0])
tb.connect(metrics_in, scale)
tb.connect(scale, (siso_in[0], 1))
# connect the rest
for it in range(IT):
if it < IT - 1:
tb.connect(metrics_in, (siso_in[it + 1], 1))
tb.connect(siso_in[it], deinter[it], (siso_out[it], 1))
tb.connect(gnd, (siso_out[it], 0))
tb.connect(siso_out[it], inter[it + 1])
tb.connect(inter[it], (siso_in[it], 0))
else:
tb.connect(siso_in[it], deinter[it], siso_out[it])
tb.connect(inter[it], (siso_in[it], 0))
return (metrics_in, siso_out[IT - 1])
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, N0, seed):
tb = gr.top_block()
# TX
src = blocks.lfsr_32k_source_s()
src_head = blocks.head(gr.sizeof_short, Kb / 16) # packet size in shorts
s2fsmi = blocks.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 = digital.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = blocks.add_ff()
noise = analog.noise_source_f(analog.GR_GAUSSIAN, math.sqrt(N0 / 2), seed)
# RX
metrics_in = trellis.metrics_f(
fi.O(), dimensionality, constellation, digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner Viterbi
gnd = blocks.vector_source_f([0], True)
siso_in = trellis.siso_f(
fi, K, 0, -1, True, False, trellis.TRELLIS_MIN_SUM
) # Put -1 if the Initial/Final states are not set.
deinter = trellis.permutation(interleaver.K(), interleaver.DEINTER(),
fi.I(), gr.sizeof_float)
va_out = trellis.viterbi_s(
fo, K, 0, -1) # Put -1 if the Initial/Final states are not set.
fsmi2s = blocks.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = blocks.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc_out, inter, enc_in, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics_in)
tb.connect(gnd, (siso_in, 0))
tb.connect(metrics_in, (siso_in, 1))
tb.connect(siso_in, deinter, va_out, fsmi2s, dst)
tb.run()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test (fo,fi,interleaver,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 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
metrics_in = trellis.metrics_f(fi.O(),dimensionality,constellation,trellis.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for innner Viterbi
gnd = gr.vector_source_f([0],True);
siso_in = trellis.siso_f(fi,K,0,-1,True,False,trellis.TRELLIS_MIN_SUM) # Put -1 if the Initial/Final states are not set.
deinter = trellis.permutation(interleaver.K(),interleaver.DEINTER(),fi.I(),gr.sizeof_float)
va_out = trellis.viterbi_s(fo,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_out,inter,enc_in,mod)
fg.connect (mod,(add,0))
fg.connect (noise,(add,1))
fg.connect (add,metrics_in)
fg.connect (gnd,(siso_in,0))
fg.connect (metrics_in,(siso_in,1))
fg.connect (siso_in,deinter,va_out,fsmi2s,dst)
fg.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def make_rx(tb,fo,fi,dimensionality,tot_constellation,K,interleaver,IT,Es,N0,type):
scale = gr.multiply_const_ff(math.sqrt(1.0/N0))
gnd = gr.vector_source_f([0],True);
inter=[]
deinter=[]
siso_in=[]
siso_out=[]
# generate all blocks
for it in range(IT):
inter.append( trellis.permutation(interleaver.K(),interleaver.INTER(),fi.I(),gr.sizeof_float) )
siso_in.append( trellis.siso_combined_f(fi,K,0,-1,True,False,type,dimensionality,tot_constellation,trellis.TRELLIS_EUCLIDEAN) )
deinter.append( trellis.permutation(interleaver.K(),interleaver.DEINTER(),fi.I(),gr.sizeof_float) )
if it < IT-1:
siso_out.append( trellis.siso_f(fo,K,0,-1,False,True,type) )
else:
siso_out.append( trellis.viterbi_s(fo,K,0,-1) ) # no soft outputs needed
# connect first stage
tb.connect (gnd,inter[0])
tb.connect (scale,(siso_in[0],1))
# connect the rest
for it in range(IT):
if it < IT-1:
tb.connect (scale,(siso_in[it+1],1))
tb.connect (siso_in[it],deinter[it],(siso_out[it],1))
tb.connect (gnd,(siso_out[it],0))
tb.connect (siso_out[it],inter[it+1])
tb.connect (inter[it],(siso_in[it],0))
else:
tb.connect (siso_in[it],deinter[it],siso_out[it])
tb.connect (inter[it],(siso_in[it],0))
return (scale,siso_out[IT-1])
