def run_test (f,Kb,bitspersymbol,K,dimensionality,tot_constellation,N0,seed):
tb = gr.top_block ()
# 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
# essentially here we implement the combination of modulation and channel as a memoryless modulation (the memory induced by the channel is hidden in the FSM)
mod = gr.chunks_to_symbols_sf(tot_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,tot_constellation,digital.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();
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics)
tb.connect (metrics,va,fsmi2s,dst)
tb.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#print ntotal,nright,runlength
return (ntotal,ntotal-nright)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,Es,N0,IT,seed):
tb = gr.top_block ()
# 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 = trellis.sccc_encoder_ss(fo,0,fi,0,interleaver,K)
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
dec = trellis.sccc_decoder_combined_fs(fo,0,-1,fi,0,-1,interleaver,K,IT,trellis.TRELLIS_MIN_SUM,dimensionality,constellation,digital.TRELLIS_EUCLIDEAN,1.0)
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
#tb.connect (src,src_head,s2fsmi,enc_out,inter,enc_in,mod)
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
#tb.connect (add,head)
#tb.connect (tail,fsmi2s,dst)
tb.connect (add,dec,fsmi2s,dst)
tb.run()
#print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,tot_constellation,N0,seed):
tb = gr.top_block ()
# 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
# essentially here we implement the combination of modulation and channel as a memoryless modulation (the memory induced by the channel is hidden in the FSM)
mod = gr.chunks_to_symbols_sf(tot_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,tot_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();
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics)
tb.connect (metrics,va,fsmi2s,dst)
tb.run()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#print ntotal,nright,runlength
return (ntotal,ntotal-nright)
def run_test(f, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed):
tb = gr.top_block()
# TX
# packet = [0]*Kb
# for i in range(Kb-1*16): # last 16 bits = 0 to drive the final state to 0
# packet[i] = random.randint(0, 1) # random 0s and 1s
# src = gr.vector_source_s(packet,False)
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16) # packet size in shorts
# b2s = gr.unpacked_to_packed_ss(1,gr.GR_MSB_FIRST) # pack bits 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, digital.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
# s2b = gr.packed_to_unpacked_ss(1,gr.GR_MSB_FIRST) # unpack shorts to bits
# dst = gr.vector_sink_s();
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc, mod)
# tb.connect (src,b2s,s2fsmi,enc,mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics)
tb.connect(metrics, va, fsmi2s, dst)
# tb.connect (metrics,va,fsmi2s,s2b,dst)
tb.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()
# ntotal = len(packet)
# if len(dst.data()) != ntotal:
# print "Error: not enough data\n"
# nright = 0;
# for i in range(ntotal):
# if packet[i]==dst.data()[i]:
# nright=nright+1
# else:
# print "Error in ", i
return (ntotal, ntotal - nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed):
tb = gr.top_block ()
# TX
#packet = [0]*Kb
#for i in range(Kb-1*16): # last 16 bits = 0 to drive the final state to 0
#packet[i] = random.randint(0, 1) # random 0s and 1s
#src = gr.vector_source_s(packet,False)
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16) # packet size in shorts
#b2s = gr.unpacked_to_packed_ss(1,gr.GR_MSB_FIRST) # pack bits 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
#s2b = gr.packed_to_unpacked_ss(1,gr.GR_MSB_FIRST) # unpack shorts to bits
#dst = gr.vector_sink_s();
dst = gr.check_lfsr_32k_s()
tb.connect (src,src_head,s2fsmi,enc,mod)
#tb.connect (src,b2s,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics)
tb.connect (metrics,va,fsmi2s,dst)
#tb.connect (metrics,va,fsmi2s,s2b,dst)
tb.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 ()
#ntotal = len(packet)
#if len(dst.data()) != ntotal:
#print "Error: not enough data\n"
#nright = 0;
#for i in range(ntotal):
#if packet[i]==dst.data()[i]:
#nright=nright+1
#else:
#print "Error in ", i
return (ntotal,ntotal-nright)
def run_test(f, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed,
P):
tb = gr.top_block()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head(gr.sizeof_short, Kb / 16 * P) # 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
s2p = gr.stream_to_streams(gr.sizeof_short, P) # serial to parallel
enc = trellis.encoder_ss(f, 0) # initiali state = 0
mod = gr.chunks_to_symbols_sf(constellation, dimensionality)
# CHANNEL
add = []
noise = []
for i in range(P):
add.append(gr.add_ff())
noise.append(gr.noise_source_f(gr.GR_GAUSSIAN, math.sqrt(N0 / 2),
seed))
# RX
metrics = trellis.metrics_f(
f.O(), dimensionality, constellation, digital.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.
p2s = gr.streams_to_stream(gr.sizeof_short, P) # parallel to serial
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, s2p)
for i in range(P):
tb.connect((s2p, i), (enc, i), (mod, i))
tb.connect((mod, i), (add[i], 0))
tb.connect(noise[i], (add[i], 1))
tb.connect(add[i], (metrics, i))
tb.connect((metrics, i), (va, i), (p2s, i))
tb.connect(p2s, fsmi2s, dst)
tb.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 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,0,0) # Put -1 if the Initial/Final states are not set.
va = trellis.viterbi_combined_s(
f, K + L, 0, 0, dimensionality, tot_constellation,
trellis.TRELLIS_EUCLIDEAN
) # using viterbi_combined_s 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 run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, N0, seed):
tb = gr.top_block()
# 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, digital.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()
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 (f,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed,P):
fg = gr.flow_graph ()
# TX
src = gr.lfsr_32k_source_s()
src_head = gr.head (gr.sizeof_short,Kb/16*P) # 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
s2p = gr.stream_to_streams(gr.sizeof_short,P) # serial to parallel
enc = trellis.encoder_ss(f,0) # initiali state = 0
mod = gr.chunks_to_symbols_sf(constellation,dimensionality)
# CHANNEL
add=[]
noise=[]
for i in range(P):
add.append(gr.add_ff())
noise.append(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.
p2s = gr.streams_to_stream(gr.sizeof_short,P) # parallel to serial
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,s2p)
for i in range(P):
fg.connect ((s2p,i),(enc,i),(mod,i))
fg.connect ((mod,i),(add[i],0))
fg.connect (noise[i],(add[i],1))
fg.connect (add[i],(metrics,i))
fg.connect ((metrics,i),(va,i),(p2s,i))
fg.connect (p2s,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 run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, Es, N0, IT, seed):
tb = gr.top_block()
# 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
#src = gr.vector_source_s([0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1],False)
enc = trellis.pccc_encoder_ss(fo, 0, fi, 0, interleaver, K)
code = gr.vector_sink_s()
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() * fo.O(), dimensionality, constellation,
digital.TRELLIS_EUCLIDEAN
) # data preprocessing to generate metrics for innner SISO
scale = gr.multiply_const_ff(1.0 / N0)
dec = trellis.pccc_decoder_s(fo, 0, -1, fi, 0, -1, interleaver, K, IT,
trellis.TRELLIS_MIN_SUM)
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect(src, src_head, s2fsmi, enc, mod)
#tb.connect (src,enc,mod)
#tb.connect(enc,code)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, metrics_in, scale, dec, fsmi2s, dst)
tb.run()
#print code.data()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test (f,Kb,bitspersymbol,K,channel,modulation,dimensionality,tot_constellation,N0,seed):
fg = gr.flow_graph ()
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()
fg.connect (src,mod)
fg.connect (mod,isi,(add,0))
fg.connect (noise,(add,1))
#fg.connect (add,metrics)
#fg.connect (metrics,va,dst)
fg.connect (add,skip,va,dst)
fg.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 run_test(fo, fi, interleaver, Kb, bitspersymbol, K, channel, modulation,
dimensionality, tot_constellation, Es, N0, IT, seed):
tb = gr.top_block()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0] * (K)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
src = gr.vector_source_s(packet, False)
enc_out = trellis.encoder_ss(fo, 0) # initial state = 0
inter = trellis.permutation(interleaver.K(), interleaver.INTER(), 1,
gr.sizeof_short)
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
(head, tail) = make_rx(tb, fo, fi, dimensionality, tot_constellation, K,
interleaver, IT, Es, N0, trellis.TRELLIS_MIN_SUM)
dst = gr.vector_sink_s()
tb.connect(src, enc_out, inter, mod)
tb.connect(mod, isi, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, head)
tb.connect(tail, dst)
tb.run()
data = dst.data()
ntotal = len(data)
nright = 0
for i in range(ntotal):
if packet[i] == data[i]:
nright = nright + 1
#else:
#print "Error in ", i
return (ntotal, ntotal - nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed):
tb = gr.top_block()
# 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
va_in = trellis.viterbi_s(fi, K, 0, -1) # Put -1 if the Initial/Final states are not set.
deinter = trellis.permutation(interleaver.K(), interleaver.DEINTER(), 1, gr.sizeof_short)
metrics_out = trellis.metrics_s(
fo.O(), 1, [0, 1, 2, 3], trellis.TRELLIS_HARD_SYMBOL
) # data preprocessing to generate metrics for outer Viterbi (hard decisions)
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()
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(metrics_in, va_in, deinter, metrics_out, 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,channel,modulation,dimensionality,tot_constellation,Es,N0,IT,seed):
tb = gr.top_block ()
L = len(channel)
# TX
# this for loop is TOO slow in python!!!
packet = [0]*(K)
random.seed(seed)
for i in range(len(packet)):
packet[i] = random.randint(0, 2**bitspersymbol - 1) # random symbols
src = gr.vector_source_s(packet,False)
enc_out = trellis.encoder_ss(fo,0) # initial state = 0
inter = trellis.permutation(interleaver.K(),interleaver.INTER(),1,gr.sizeof_short)
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
(head,tail) = make_rx(tb,fo,fi,dimensionality,tot_constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_MIN_SUM)
dst = gr.vector_sink_s();
tb.connect (src,enc_out,inter,mod)
tb.connect (mod,isi,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,head)
tb.connect (tail,dst)
tb.run()
data = dst.data()
ntotal = len(data)
nright=0
for i in range(ntotal):
if packet[i]==data[i]:
nright=nright+1
#else:
#print "Error in ", i
return (ntotal,ntotal-nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, Es, N0, IT, seed):
tb = gr.top_block()
# 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(tb, fo, fi, dimensionality, constellation, K,
interleaver, IT, Es, N0, trellis.TRELLIS_MIN_SUM)
#(head,tail) = make_rx(tb,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()
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, head)
tb.connect(tail, fsmi2s, dst)
tb.run()
#print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality,
constellation, Es, N0, IT, seed):
tb = gr.top_block()
# 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 = trellis.sccc_encoder_ss(fo, 0, fi, 0, interleaver, K)
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
dec = trellis.sccc_decoder_combined_fs(fo, 0, -1, fi, 0, -1, interleaver,
K, IT, trellis.TRELLIS_MIN_SUM,
dimensionality, constellation,
digital.TRELLIS_EUCLIDEAN, 1.0)
fsmi2s = gr.unpacked_to_packed_ss(
bitspersymbol, gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
#tb.connect (src,src_head,s2fsmi,enc_out,inter,enc_in,mod)
tb.connect(src, src_head, s2fsmi, enc, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
#tb.connect (add,head)
#tb.connect (tail,fsmi2s,dst)
tb.connect(add, dec, fsmi2s, dst)
tb.run()
#print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test(f, Kb, bitspersymbol, K, dimensionality, constellation, N0, seed):
tb = gr.top_block()
# 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
va = trellis.viterbi_combined_fs(
f, K, 0, -1, dimensionality, constellation, trellis.TRELLIS_EUCLIDEAN
) # 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()
tb.connect(src, src_head, s2fsmi, enc, mod)
tb.connect(mod, (add, 0))
tb.connect(noise, (add, 1))
tb.connect(add, va, fsmi2s, dst)
tb.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 run_test(fo, fi, interleaver, Kb, bitspersymbol, K, dimensionality, constellation, Es, N0, IT, seed):
tb = gr.top_block()
# 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(
tb, fo, fi, dimensionality, constellation, K, interleaver, IT, Es, N0, trellis.TRELLIS_MIN_SUM
)
# (head,tail) = make_rx(tb,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()
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, head)
tb.connect(tail, fsmi2s, dst)
tb.run()
# print enc_out.ST(), enc_in.ST()
ntotal = dst.ntotal()
nright = dst.nright()
runlength = dst.runlength()
return (ntotal, ntotal - nright)
def run_test (f,Kb,bitspersymbol,K,dimensionality,constellation,N0,seed):
tb = gr.top_block ()
# 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
va = trellis.viterbi_combined_fs(f,K,0,-1,dimensionality,constellation,digital.TRELLIS_EUCLIDEAN) # 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();
tb.connect (src,src_head,s2fsmi,enc,mod)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,va,fsmi2s,dst)
tb.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 run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,constellation,Es,N0,IT,seed):
tb = gr.top_block ()
# 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
#src = gr.vector_source_s([0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1],False)
enc = trellis.pccc_encoder_ss(fo,0,fi,0,interleaver,K)
code = gr.vector_sink_s()
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()*fo.O(),dimensionality,constellation,digital.TRELLIS_EUCLIDEAN) # data preprocessing to generate metrics for innner SISO
scale = gr.multiply_const_ff(1.0/N0)
dec = trellis.pccc_decoder_s(fo,0,-1,fi,0,-1,interleaver,K,IT,trellis.TRELLIS_MIN_SUM)
fsmi2s = gr.unpacked_to_packed_ss(bitspersymbol,gr.GR_MSB_FIRST) # pack FSM input symbols to shorts
dst = gr.check_lfsr_32k_s()
tb.connect (src,src_head,s2fsmi,enc,mod)
#tb.connect (src,enc,mod)
#tb.connect(enc,code)
tb.connect (mod,(add,0))
tb.connect (noise,(add,1))
tb.connect (add,metrics_in,scale,dec,fsmi2s,dst)
tb.run()
#print code.data()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
return (ntotal,ntotal-nright)
def run_test (fo,fi,interleaver,Kb,bitspersymbol,K,dimensionality,tot_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 iouter 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
# essentially here we implement the combination of modulation and channel as a memoryless modulation (the memory induced by the channel is hidden in the innner FSM)
mod = gr.chunks_to_symbols_sf(tot_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,tot_constellation,K,interleaver,IT,Es,N0,trellis.TRELLIS_MIN_SUM)
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()
ntotal = dst.ntotal ()
nright = dst.nright ()
runlength = dst.runlength ()
#print ntotal,nright,runlength
return (ntotal,ntotal-nright)
