int main(void)
{
//general parameters
double threshold_value = 50;
string map_metric="logMAP";
ivec gen = "037 021";//octal form
int constraint_length = 5;
int nb_errors_lim = 1500;
int nb_bits_lim = int(1e6);
int perm_len = pow2i(14);//permutation length
int nb_iter = 10;//number of iterations in the turbo decoder
vec EbN0_dB = "0:0.1:5";
double R = 1.0/4.0;//coding rate (non punctured SCCC)
double Ec = 1.0;//coded bit energy
//other parameters
string filename = "Res/sccc_"+map_metric+".it";
int nb_bits_tail = perm_len/gen.length();
int nb_bits = nb_bits_tail-(constraint_length-1);//number of bits in a block (without tail)
vec sigma2 = (0.5*Ec/R)*pow(inv_dB(EbN0_dB), -1.0);//N0/2
double Lc;//scaling factor for intrinsic information
int nb_blocks;//number of blocks
int nb_errors;
bvec bits(nb_bits);//data bits
bvec nsc_coded_bits;//tail is added
bmat rsc_parity_bits;
ivec perm(perm_len);
ivec inv_perm(perm_len);
int rec_len = gen.length()*perm_len;
bvec coded_bits(rec_len);
vec rec(rec_len);
//SISO RSC
vec rsc_intrinsic_coded(rec_len);
vec rsc_apriori_data(perm_len);
vec rsc_extrinsic_coded;
vec rsc_extrinsic_data;
//SISO NSC
vec nsc_intrinsic_coded(perm_len);
vec nsc_apriori_data(nb_bits_tail);
nsc_apriori_data.zeros();//always zero
vec nsc_extrinsic_coded;
vec nsc_extrinsic_data;
//decision
bvec rec_bits(nb_bits_tail);
int snr_len = EbN0_dB.length();
mat ber(nb_iter,snr_len);
ber.zeros();
register int en,n;
//Non recursive non Systematic Convolutional Code
Convolutional_Code nsc;
nsc.set_generator_polynomials(gen, constraint_length);
//Recursive Systematic Convolutional Code
Rec_Syst_Conv_Code rsc;
rsc.set_generator_polynomials(gen, constraint_length);//initial state should be the zero state
//BPSK modulator
BPSK bpsk;
//AWGN channel
AWGN_Channel channel;
//SISO blocks
SISO siso;
siso.set_generators(gen, constraint_length);
siso.set_map_metric(map_metric);
//BER
BERC berc;
//Progress timer
tr::Progress_Timer timer;
timer.set_max(snr_len);
//Randomize generators
RNG_randomize();
//main loop
timer.progress(0.0);
for (en=0;en<snr_len;en++)
{
channel.set_noise(sigma2(en));
Lc = -2.0/sigma2(en);//take into account the BPSK mapping
nb_errors = 0;
nb_blocks = 0;
while ((nb_errors<nb_errors_lim) && (nb_blocks*nb_bits<nb_bits_lim))//if at the last iteration the nb. of errors is inferior to lim, then process another block
{
//permutation
perm = sort_index(randu(perm_len));
//inverse permutation
inv_perm = sort_index(perm);
//bits generation
bits = randb(nb_bits);
//serial concatenated convolutional code
nsc.encode_tail(bits, nsc_coded_bits);//tail is added here to information bits to close the trellis
nsc_coded_bits = nsc_coded_bits(perm);//interleave
rsc.encode(nsc_coded_bits, rsc_parity_bits);//no tail added
for(n=0;n<perm_len;n++)
{
coded_bits(2*n) = nsc_coded_bits(n);//systematic output
coded_bits(2*n+1) = rsc_parity_bits(n,0);//parity output
}
//BPSK modulation (1->-1,0->+1) + channel
rec = channel(bpsk.modulate_bits(coded_bits));
//turbo decoder
rsc_intrinsic_coded = Lc*rec;//intrinsic information of coded bits
rsc_apriori_data.zeros();//a priori LLR for information bits
for (n=0;n<nb_iter;n++)
{
//first decoder
siso.rsc(rsc_extrinsic_coded, rsc_extrinsic_data, rsc_intrinsic_coded, rsc_apriori_data, false);
//deinterleave+threshold
nsc_intrinsic_coded = threshold(rsc_extrinsic_data(inv_perm), threshold_value);
//second decoder
siso.nsc(nsc_extrinsic_coded, nsc_extrinsic_data, nsc_intrinsic_coded, nsc_apriori_data, true);
//decision
rec_bits = bpsk.demodulate_bits(-nsc_extrinsic_data);//suppose that a priori info is zero
//count errors
berc.clear();
berc.count(bits, rec_bits.left(nb_bits));
ber(n,en) += berc.get_errorrate();
//interleave
rsc_apriori_data = nsc_extrinsic_coded(perm);
}//end iterations
nb_errors += int(berc.get_errors());//get number of errors at the last iteration
nb_blocks++;
}//end blocks (while loop)
//compute BER over all tx blocks
ber.set_col(en, ber.get_col(en)/nb_blocks);
//show progress
timer.progress(1+en);
}
timer.toc_print();
#ifdef TO_FILE
//save results to file
it_file ff(filename);
ff << Name("BER") << ber;
ff << Name("EbN0_dB") << EbN0_dB;
ff << Name("gen") << gen;
ff << Name("R") << R;
ff << Name("nb_iter") << nb_iter;
ff << Name("total_nb_bits") << nb_bits;
ff << Name("nb_errors_lim") << nb_errors_lim;
ff << Name("nb_bits_lim") << nb_bits_lim;
ff.close();
#else
//show BER
cout << ber << endl;
#endif
return 0;
}
int main(void)
{
//general parameters
double threshold_value = 10;
string map_metric="maxlogMAP";
ivec gen = "07 05";//octal form, feedback first
int constraint_length = 3;
int nb_errors_lim = 3000;
int nb_bits_lim = int(1e6);
int perm_len = (1<<14);//total number of bits in a block (with tail)
int nb_iter = 10;//number of iterations in the turbo decoder
vec EbN0_dB = "0:0.1:5";
double R = 1.0/3.0;//coding rate (non punctured PCCC)
double Ec = 1.0;//coded bit energy
//other parameters
int nb_bits = perm_len-(constraint_length-1);//number of bits in a block (without tail)
vec sigma2 = (0.5*Ec/R)*pow(inv_dB(EbN0_dB), -1.0);//N0/2
double Lc;//scaling factor
int nb_blocks;//number of blocks
int nb_errors;
ivec perm(perm_len);
ivec inv_perm(perm_len);
bvec bits(nb_bits);
int cod_bits_len = perm_len*gen.length();
bmat cod1_bits;//tail is added
bvec tail;
bvec cod2_input;
bmat cod2_bits;
int rec_len = int(1.0/R)*perm_len;
bvec coded_bits(rec_len);
vec rec(rec_len);
vec dec1_intrinsic_coded(cod_bits_len);
vec dec2_intrinsic_coded(cod_bits_len);
vec apriori_data(perm_len);//a priori LLR for information bits
vec extrinsic_coded(perm_len);
vec extrinsic_data(perm_len);
bvec rec_bits(perm_len);
int snr_len = EbN0_dB.length();
mat ber(nb_iter,snr_len);
ber.zeros();
register int en,n;
//Recursive Systematic Convolutional Code
Rec_Syst_Conv_Code cc;
cc.set_generator_polynomials(gen, constraint_length);//initial state should be the zero state
//BPSK modulator
BPSK bpsk;
//AWGN channel
AWGN_Channel channel;
//SISO modules
SISO siso;
siso.set_generators(gen, constraint_length);
siso.set_map_metric(map_metric);
//BER
BERC berc;
//Randomize generators
RNG_randomize();
//main loop
for (en=0;en<snr_len;en++)
{
cout << "EbN0_dB = " << EbN0_dB(en) << endl;
channel.set_noise(sigma2(en));
Lc = -2/sigma2(en);//normalisation factor for intrinsic information (take into account the BPSK mapping)
nb_errors = 0;
nb_blocks = 0;
while ((nb_errors<nb_errors_lim) && (nb_blocks*nb_bits<nb_bits_lim))
{
//permutation
perm = sort_index(randu(perm_len));
//inverse permutation
inv_perm = sort_index(perm);
//bits generation
bits = randb(nb_bits);
//parallel concatenated convolutional code
cc.encode_tail(bits, tail, cod1_bits);//tail is added here to information bits to close the trellis
cod2_input = concat(bits, tail);
cc.encode(cod2_input(perm), cod2_bits);
for (n=0;n<perm_len;n++)//output with no puncturing
{
coded_bits(3*n) = cod2_input(n);//systematic output
coded_bits(3*n+1) = cod1_bits(n,0);//first parity output
coded_bits(3*n+2) = cod2_bits(n,0);//second parity output
}
//BPSK modulation (1->-1,0->+1) + AWGN channel
rec = channel(bpsk.modulate_bits(coded_bits));
//form input for SISO blocks
for (n=0;n<perm_len;n++)
{
dec1_intrinsic_coded(2*n) = Lc*rec(3*n);
dec1_intrinsic_coded(2*n+1) = Lc*rec(3*n+1);
dec2_intrinsic_coded(2*n) = 0.0;//systematic output of the CC is already used in decoder1
dec2_intrinsic_coded(2*n+1) = Lc*rec(3*n+2);
}
//turbo decoder
apriori_data.zeros();//a priori LLR for information bits
for (n=0;n<nb_iter;n++)
{
//first decoder (terminated trellis)
siso.rsc(extrinsic_coded, extrinsic_data, dec1_intrinsic_coded, apriori_data, true);
//interleave
apriori_data = extrinsic_data(perm);
//threshold
apriori_data = SISO::threshold(apriori_data, threshold_value);
//second decoder (unterminated trellis)
siso.rsc(extrinsic_coded, extrinsic_data, dec2_intrinsic_coded, apriori_data);
//decision
apriori_data += extrinsic_data;//a posteriori information
rec_bits = bpsk.demodulate_bits(-apriori_data(inv_perm));//take into account the BPSK mapping
//count errors
berc.clear();
berc.count(bits, rec_bits.left(nb_bits));
ber(n,en) += berc.get_errorrate();
//deinterleave for the next iteration
apriori_data = extrinsic_data(inv_perm);
}//end iterations
nb_errors += int(berc.get_errors());//get number of errors at the last iteration
nb_blocks++;
}//end blocks (while loop)
//compute BER over all tx blocks
ber.set_col(en, ber.get_col(en)/nb_blocks);
}
it_file ff("pccc_bersim_awgn.it");
ff << Name("EbN0_dB") << EbN0_dB;
ff << Name("BER") << ber;
ff.close();
return 0;
}
TEST(SISO, all)
{
//general parameters
string map_metric="maxlogMAP";
ivec gen = "07 05";//octal form, feedback first
int constraint_length = 3;
int nb_errors_lim = 300;
int nb_bits_lim = int(1e4);
int perm_len = (1<<14);//total number of bits in a block (with tail)
int nb_iter = 10;//number of iterations in the turbo decoder
vec EbN0_dB = "0.0 0.5 1.0 1.5 2.0";
double R = 1.0/3.0;//coding rate (non punctured PCCC)
double Ec = 1.0;//coded bit energy
//other parameters
int nb_bits = perm_len-(constraint_length-1);//number of bits in a block (without tail)
vec sigma2 = (0.5*Ec/R)*pow(inv_dB(EbN0_dB), -1.0);//N0/2
double Lc;//scaling factor
int nb_blocks;//number of blocks
int nb_errors;
ivec perm(perm_len);
ivec inv_perm(perm_len);
bvec bits(nb_bits);
int cod_bits_len = perm_len*gen.length();
bmat cod1_bits;//tail is added
bvec tail;
bvec cod2_input;
bmat cod2_bits;
int rec_len = int(1.0/R)*perm_len;
bvec coded_bits(rec_len);
vec rec(rec_len);
vec dec1_intrinsic_coded(cod_bits_len);
vec dec2_intrinsic_coded(cod_bits_len);
vec apriori_data(perm_len);//a priori LLR for information bits
vec extrinsic_coded(perm_len);
vec extrinsic_data(perm_len);
bvec rec_bits(perm_len);
int snr_len = EbN0_dB.length();
mat ber(nb_iter,snr_len);
ber.zeros();
register int en,n;
//Recursive Systematic Convolutional Code
Rec_Syst_Conv_Code cc;
cc.set_generator_polynomials(gen, constraint_length);//initial state should be the zero state
//BPSK modulator
BPSK bpsk;
//AWGN channel
AWGN_Channel channel;
//SISO modules
SISO siso;
siso.set_generators(gen, constraint_length);
siso.set_map_metric(map_metric);
//BER
BERC berc;
//Fix random generators
RNG_reset(12345);
//main loop
for (en=0;en<snr_len;en++)
{
channel.set_noise(sigma2(en));
Lc = -2/sigma2(en);//normalisation factor for intrinsic information (take into account the BPSK mapping)
nb_errors = 0;
nb_blocks = 0;
while ((nb_errors<nb_errors_lim) && (nb_blocks*nb_bits<nb_bits_lim))//if at the last iteration the nb. of errors is inferior to lim, then process another block
{
//permutation
perm = sort_index(randu(perm_len));
//inverse permutation
inv_perm = sort_index(perm);
//bits generation
bits = randb(nb_bits);
//parallel concatenated convolutional code
cc.encode_tail(bits, tail, cod1_bits);//tail is added here to information bits to close the trellis
cod2_input = concat(bits, tail);
cc.encode(cod2_input(perm), cod2_bits);
for (n=0;n<perm_len;n++)//output with no puncturing
{
coded_bits(3*n) = cod2_input(n);//systematic output
coded_bits(3*n+1) = cod1_bits(n,0);//first parity output
coded_bits(3*n+2) = cod2_bits(n,0);//second parity output
}
//BPSK modulation (1->-1,0->+1) + AWGN channel
rec = channel(bpsk.modulate_bits(coded_bits));
//form input for SISO blocks
for (n=0;n<perm_len;n++)
{
dec1_intrinsic_coded(2*n) = Lc*rec(3*n);
dec1_intrinsic_coded(2*n+1) = Lc*rec(3*n+1);
dec2_intrinsic_coded(2*n) = 0.0;//systematic output of the CC is already used in decoder1
dec2_intrinsic_coded(2*n+1) = Lc*rec(3*n+2);
}
//turbo decoder
apriori_data.zeros();//a priori LLR for information bits
for (n=0;n<nb_iter;n++)
{
//first decoder
siso.rsc(extrinsic_coded, extrinsic_data, dec1_intrinsic_coded, apriori_data, true);
//interleave
apriori_data = extrinsic_data(perm);
//second decoder
siso.rsc(extrinsic_coded, extrinsic_data, dec2_intrinsic_coded, apriori_data, false);
//decision
apriori_data += extrinsic_data;//a posteriori information
rec_bits = bpsk.demodulate_bits(-apriori_data(inv_perm));//take into account the BPSK mapping
//count errors
berc.clear();
berc.count(bits, rec_bits.left(nb_bits));
ber(n,en) += berc.get_errorrate();
//deinterleave for the next iteration
apriori_data = extrinsic_data(inv_perm);
}//end iterations
nb_errors += int(berc.get_errors());//get number of errors at the last iteration
nb_blocks++;
}//end blocks (while loop)
//compute BER over all tx blocks
ber.set_col(en, ber.get_col(en)/nb_blocks);
}
// Results for max log MAP algorithm
vec ref = "0.158039 0.110731 0.0770358 0.0445611 0.0235014";
assert_vec(ref, ber.get_row(0));
ref = "0.14168 0.0783177 0.0273471 0.00494445 0.00128189";
assert_vec(ref, ber.get_row(1));
ref = "0.141375 0.0565865 0.00817971 0.000305213 0";
assert_vec(ref, ber.get_row(2));
ref = "0.142412 0.0421194 0.000732511 0 0";
assert_vec(ref, ber.get_row(3));
ref = "0.144244 0.0282017 0.000183128 0 0";
assert_vec(ref, ber.get_row(4));
ref = "0.145587 0.0142229 0 0 0";
assert_vec(ref, ber.get_row(5));
ref = "0.148517 0.00714199 0 0 0";
assert_vec(ref, ber.get_row(6));
ref = "0.141619 0.00225858 0 0 0";
assert_vec(ref, ber.get_row(7));
ref = "0.149676 0.000549383 0 0 0";
assert_vec(ref, ber.get_row(8));
ref = "0.14461 0 0 0 0";
assert_vec(ref, ber.get_row(9));
}