Simulation of SCCCs in an AWGN channel

This program simulates Serially Concatenated Convolutional Codes (SCCCs) of coding rate 1/4 using a turbo decoder with a SISO NSC module and a SISO RSC module.

Reference: S. Benedetto, D. Divsalar, G. Motorsi and F. Pollara, "A Soft-Input Soft-Output Maximum A posteriori (MAP) Module to Decode Parallel and Serial Concatenated Codes", TDA Progress Report, nov. 1996

#include "itpp/itcomm.h"
using namespace itpp;
using std::cout;
using std::endl;
using std::string;
int main(void)
{
//general parameters
double threshold_value = 50;
string map_metric = "maxlogMAP";
ivec gen = "07 05";//octal form
int constraint_length = 3;
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
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;
//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 = -2.0 / 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 = SISO::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);
}
//save results to file
it_file ff("sccc_bersim_awgn.it");
ff << Name("BER") << ber;
ff << Name("EbN0_dB") << EbN0_dB;
ff.close();
return 0;
}
itpp::AWGN_Channel
Ordinary AWGN Channel for cvec or vec inputs and outputs.
Definition channel.h:1089
itpp::Array
General array class.
Definition array.h:105
itpp::Array::left
Array< T > left(int n) const
Get n left elements of the array.
Definition array.h:357
itpp::Array::length
int length() const
Returns the number of data elements in the array object.
Definition array.h:157
itpp::BERC
Bit Error Rate Counter (BERC) Class.
Definition error_counters.h:68
itpp::BPSK
BPSK modulator with real symbols.
Definition modulator.h:877
itpp::BPSK::modulate_bits
void modulate_bits(const bvec &bits, vec &output) const
Modulate bits into BPSK symbols in complex domain.
Definition modulator.cpp:310
itpp::BPSK::demodulate_bits
void demodulate_bits(const vec &signal, bvec &output) const
Demodulate noisy BPSK symbols in complex domain into bits.
Definition modulator.cpp:326
itpp::Convolutional_Code
Binary Convolutional rate 1/n class.
Definition convcode.h:105
itpp::Convolutional_Code::encode_tail
void encode_tail(const bvec &input, bvec &output)
Encoding that starts and ends in the zero state.
Definition convcode.cpp:662
itpp::Convolutional_Code::set_generator_polynomials
void set_generator_polynomials(const ivec &gen, int constraint_length)
Set generator polynomials. Given in Proakis integer form.
Definition convcode.cpp:555
itpp::Name
Automatic naming when saving.
Definition itfile.h:429
itpp::Rec_Syst_Conv_Code
A Recursive Systematic Convolutional Encoder/Decoder class.
Definition rec_syst_conv_code.h:52
itpp::Rec_Syst_Conv_Code::set_generator_polynomials
void set_generator_polynomials(const ivec &gen, int constraint_length)
Set generator polynomials.
Definition rec_syst_conv_code.cpp:69
itpp::Rec_Syst_Conv_Code::encode
void encode(const bvec &input, bmat &parity_bits)
Encode a binary vector of inputs starting from zero state without adding of a tail.
Definition rec_syst_conv_code.cpp:151
itpp::SISO
Soft Input Soft Output (SISO) modules.
Definition siso.h:72
itpp::it_file
The IT++ file format reading and writing class.
Definition itfile.h:246
itcomm.h
Include file for the IT++ communications module.
bmat
Mat< bin > bmat
bin matrix
Definition mat.h:508
itpp
itpp namespace
Definition itmex.h:37

When you run this program, the results (BER and EbN0_dB) are saved into sccc_bersim_awgn.it file. Using the following MATLAB script

clear all
itload('sccc_bersim_awgn.it');
figure
semilogy(EbN0_dB, BER, 'o-')
grid on
xlabel('E_b/N_0 [dB]')
ylabel('BER')

the results can be displayed.

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