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core_algorithms.cc
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/* -*- c++ -*- */
/*
* Copyright 2004,2012 Free Software Foundation, Inc.
*
* This file is part of GNU Radio
*
* SPDX-License-Identifier: GPL-3.0-or-later
*
*/
#include <gnuradio/trellis/calc_metric.h>
#include <gnuradio/trellis/core_algorithms.h>
#include <cstring>
#include <stdexcept>
namespace gr {
namespace trellis {
static const float INF = 1.0e9;
float min(float a, float b) { return a <= b ? a : b; }
float min_star(float a, float b)
{
return (a <= b ? a : b) - log(1 + exp(a <= b ? a - b : b - a));
}
template <class T>
void viterbi_algorithm(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
const float* in,
T* out) //,
// std::vector<int> &trace)
{
std::vector<int> trace(S * K);
std::vector<float> alpha(S * 2);
int alphai;
float norm, mm, minm;
int minmi;
int st;
if (S0 < 0) { // initial state not specified
for (int i = 0; i < S; i++)
alpha[0 * S + i] = 0;
} else {
for (int i = 0; i < S; i++)
alpha[0 * S + i] = INF;
alpha[0 * S + S0] = 0.0;
}
alphai = 0;
for (int k = 0; k < K; k++) {
norm = INF;
for (int j = 0; j < S; j++) { // for each next state do ACS
minm = INF;
minmi = 0;
for (unsigned int i = 0; i < PS[j].size(); i++) {
// int i0 = j*I+i;
if ((mm = alpha[alphai * S + PS[j][i]] +
in[k * O + OS[PS[j][i] * I + PI[j][i]]]) < minm)
minm = mm, minmi = i;
}
trace[k * S + j] = minmi;
alpha[((alphai + 1) % 2) * S + j] = minm;
if (minm < norm)
norm = minm;
}
for (int j = 0; j < S; j++)
alpha[((alphai + 1) % 2) * S + j] -=
norm; // normalize total metrics so they do not explode
alphai = (alphai + 1) % 2;
}
if (SK < 0) { // final state not specified
minm = INF;
minmi = 0;
for (int i = 0; i < S; i++)
if ((mm = alpha[alphai * S + i]) < minm)
minm = mm, minmi = i;
st = minmi;
} else {
st = SK;
}
for (int k = K - 1; k >= 0; k--) { // traceback
int i0 = trace[k * S + st];
out[k] = (T)PI[st][i0];
st = PS[st][i0];
}
}
template void viterbi_algorithm<unsigned char>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
const float* in,
unsigned char* out);
template void viterbi_algorithm<short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
const float* in,
short* out);
template void viterbi_algorithm<int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
const float* in,
int* out);
//==============================================
template <class Ti, class To>
void viterbi_algorithm_combined(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<Ti>& TABLE,
digital::trellis_metric_type_t TYPE,
const Ti* in,
To* out)
{
std::vector<int> trace(S * K);
std::vector<float> alpha(S * 2);
std::vector<float> metric(O);
int alphai;
float norm, mm, minm;
int minmi;
int st;
if (S0 < 0) { // initial state not specified
for (int i = 0; i < S; i++)
alpha[0 * S + i] = 0;
} else {
for (int i = 0; i < S; i++)
alpha[0 * S + i] = INF;
alpha[0 * S + S0] = 0.0;
}
alphai = 0;
for (int k = 0; k < K; k++) {
calc_metric(O, D, TABLE, &(in[k * D]), metric.data(), TYPE); // calc metrics
norm = INF;
for (int j = 0; j < S; j++) { // for each next state do ACS
minm = INF;
minmi = 0;
for (unsigned int i = 0; i < PS[j].size(); i++) {
// int i0 = j*I+i;
if ((mm = alpha[alphai * S + PS[j][i]] +
metric[OS[PS[j][i] * I + PI[j][i]]]) < minm)
minm = mm, minmi = i;
}
trace[k * S + j] = minmi;
alpha[((alphai + 1) % 2) * S + j] = minm;
if (minm < norm)
norm = minm;
}
for (int j = 0; j < S; j++)
alpha[((alphai + 1) % 2) * S + j] -=
norm; // normalize total metrics so they do not explode
alphai = (alphai + 1) % 2;
}
if (SK < 0) { // final state not specified
minm = INF;
minmi = 0;
for (int i = 0; i < S; i++)
if ((mm = alpha[alphai * S + i]) < minm)
minm = mm, minmi = i;
st = minmi;
} else {
st = SK;
}
for (int k = K - 1; k >= 0; k--) { // traceback
int i0 = trace[k * S + st];
out[k] = (To)PI[st][i0];
st = PS[st][i0];
}
}
// Ti = s i f c
// To = b s i
//---------------
template void
viterbi_algorithm_combined<char, unsigned char>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<char>& TABLE,
digital::trellis_metric_type_t TYPE,
const char* in,
unsigned char* out);
template void
viterbi_algorithm_combined<short, unsigned char>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<short>& TABLE,
digital::trellis_metric_type_t TYPE,
const short* in,
unsigned char* out);
template void
viterbi_algorithm_combined<int, unsigned char>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<int>& TABLE,
digital::trellis_metric_type_t TYPE,
const int* in,
unsigned char* out);
template void
viterbi_algorithm_combined<float, unsigned char>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<float>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* in,
unsigned char* out);
template void viterbi_algorithm_combined<gr_complex, unsigned char>(
int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<gr_complex>& TABLE,
digital::trellis_metric_type_t TYPE,
const gr_complex* in,
unsigned char* out);
//---------------
template void
viterbi_algorithm_combined<char, short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<char>& TABLE,
digital::trellis_metric_type_t TYPE,
const char* in,
short* out);
template void
viterbi_algorithm_combined<short, short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<short>& TABLE,
digital::trellis_metric_type_t TYPE,
const short* in,
short* out);
template void
viterbi_algorithm_combined<int, short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<int>& TABLE,
digital::trellis_metric_type_t TYPE,
const int* in,
short* out);
template void
viterbi_algorithm_combined<float, short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<float>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* in,
short* out);
template void
viterbi_algorithm_combined<gr_complex, short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<gr_complex>& TABLE,
digital::trellis_metric_type_t TYPE,
const gr_complex* in,
short* out);
//--------------
template void
viterbi_algorithm_combined<char, int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<char>& TABLE,
digital::trellis_metric_type_t TYPE,
const char* in,
int* out);
template void
viterbi_algorithm_combined<short, int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<short>& TABLE,
digital::trellis_metric_type_t TYPE,
const short* in,
int* out);
template void
viterbi_algorithm_combined<int, int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<int>& TABLE,
digital::trellis_metric_type_t TYPE,
const int* in,
int* out);
template void
viterbi_algorithm_combined<float, int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<float>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* in,
int* out);
template void
viterbi_algorithm_combined<gr_complex, int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
int D,
const std::vector<gr_complex>& TABLE,
digital::trellis_metric_type_t TYPE,
const gr_complex* in,
int* out);
//===============================================
void siso_algorithm(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
bool POSTI,
bool POSTO,
float (*p2mymin)(float, float),
const float* priori,
const float* prioro,
float* post //,
// std::vector<float> &alpha,
// std::vector<float> &beta
)
{
float norm, mm, minm;
std::vector<float> alpha(S * (K + 1));
std::vector<float> beta(S * (K + 1));
if (S0 < 0) { // initial state not specified
for (int i = 0; i < S; i++)
alpha[0 * S + i] = 0;
} else {
for (int i = 0; i < S; i++)
alpha[0 * S + i] = INF;
alpha[0 * S + S0] = 0.0;
}
for (int k = 0; k < K; k++) { // forward recursion
norm = INF;
for (int j = 0; j < S; j++) {
minm = INF;
for (unsigned int i = 0; i < PS[j].size(); i++) {
// int i0 = j*I+i;
mm = alpha[k * S + PS[j][i]] + priori[k * I + PI[j][i]] +
prioro[k * O + OS[PS[j][i] * I + PI[j][i]]];
minm = (*p2mymin)(minm, mm);
}
alpha[(k + 1) * S + j] = minm;
if (minm < norm)
norm = minm;
}
for (int j = 0; j < S; j++)
alpha[(k + 1) * S + j] -=
norm; // normalize total metrics so they do not explode
}
if (SK < 0) { // final state not specified
for (int i = 0; i < S; i++)
beta[K * S + i] = 0;
} else {
for (int i = 0; i < S; i++)
beta[K * S + i] = INF;
beta[K * S + SK] = 0.0;
}
for (int k = K - 1; k >= 0; k--) { // backward recursion
norm = INF;
for (int j = 0; j < S; j++) {
minm = INF;
for (int i = 0; i < I; i++) {
int i0 = j * I + i;
mm = beta[(k + 1) * S + NS[i0]] + priori[k * I + i] +
prioro[k * O + OS[i0]];
minm = (*p2mymin)(minm, mm);
}
beta[k * S + j] = minm;
if (minm < norm)
norm = minm;
}
for (int j = 0; j < S; j++)
beta[k * S + j] -= norm; // normalize total metrics so they do not explode
}
if (POSTI && POSTO) {
for (int k = 0; k < K; k++) { // input combining
norm = INF;
for (int i = 0; i < I; i++) {
minm = INF;
for (int j = 0; j < S; j++) {
mm = alpha[k * S + j] + prioro[k * O + OS[j * I + i]] +
beta[(k + 1) * S + NS[j * I + i]];
minm = (*p2mymin)(minm, mm);
}
post[k * (I + O) + i] = minm;
if (minm < norm)
norm = minm;
}
for (int i = 0; i < I; i++)
post[k * (I + O) + i] -= norm; // normalize metrics
}
for (int k = 0; k < K; k++) { // output combining
norm = INF;
for (int n = 0; n < O; n++) {
minm = INF;
for (int j = 0; j < S; j++) {
for (int i = 0; i < I; i++) {
mm = (n == OS[j * I + i] ? alpha[k * S + j] + priori[k * I + i] +
beta[(k + 1) * S + NS[j * I + i]]
: INF);
minm = (*p2mymin)(minm, mm);
}
}
post[k * (I + O) + I + n] = minm;
if (minm < norm)
norm = minm;
}
for (int n = 0; n < O; n++)
post[k * (I + O) + I + n] -= norm; // normalize metrics
}
} else if (POSTI) {
for (int k = 0; k < K; k++) { // input combining
norm = INF;
for (int i = 0; i < I; i++) {
minm = INF;
for (int j = 0; j < S; j++) {
mm = alpha[k * S + j] + prioro[k * O + OS[j * I + i]] +
beta[(k + 1) * S + NS[j * I + i]];
minm = (*p2mymin)(minm, mm);
}
post[k * I + i] = minm;
if (minm < norm)
norm = minm;
}
for (int i = 0; i < I; i++)
post[k * I + i] -= norm; // normalize metrics
}
} else if (POSTO) {
for (int k = 0; k < K; k++) { // output combining
norm = INF;
for (int n = 0; n < O; n++) {
minm = INF;
for (int j = 0; j < S; j++) {
for (int i = 0; i < I; i++) {
mm = (n == OS[j * I + i] ? alpha[k * S + j] + priori[k * I + i] +
beta[(k + 1) * S + NS[j * I + i]]
: INF);
minm = (*p2mymin)(minm, mm);
}
}
post[k * O + n] = minm;
if (minm < norm)
norm = minm;
}
for (int n = 0; n < O; n++)
post[k * O + n] -= norm; // normalize metrics
}
} else
throw std::runtime_error("Not both POSTI and POSTO can be false.");
}
//===========================================================
template <class T>
void siso_algorithm_combined(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
bool POSTI,
bool POSTO,
float (*p2mymin)(float, float),
int D,
const std::vector<T>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* priori,
const T* observations,
float* post)
{
float norm, mm, minm;
std::vector<float> alpha(S * (K + 1));
std::vector<float> beta(S * (K + 1));
std::vector<float> prioro(O * K);
if (S0 < 0) { // initial state not specified
for (int i = 0; i < S; i++)
alpha[0 * S + i] = 0;
} else {
for (int i = 0; i < S; i++)
alpha[0 * S + i] = INF;
alpha[0 * S + S0] = 0.0;
}
for (int k = 0; k < K; k++) { // forward recursion
calc_metric(
O, D, TABLE, &(observations[k * D]), &(prioro[k * O]), TYPE); // calc metrics
norm = INF;
for (int j = 0; j < S; j++) {
minm = INF;
for (unsigned int i = 0; i < PS[j].size(); i++) {
// int i0 = j*I+i;
mm = alpha[k * S + PS[j][i]] + priori[k * I + PI[j][i]] +
prioro[k * O + OS[PS[j][i] * I + PI[j][i]]];
minm = (*p2mymin)(minm, mm);
}
alpha[(k + 1) * S + j] = minm;
if (minm < norm)
norm = minm;
}
for (int j = 0; j < S; j++)
alpha[(k + 1) * S + j] -=
norm; // normalize total metrics so they do not explode
}
if (SK < 0) { // final state not specified
for (int i = 0; i < S; i++)
beta[K * S + i] = 0;
} else {
for (int i = 0; i < S; i++)
beta[K * S + i] = INF;
beta[K * S + SK] = 0.0;
}
for (int k = K - 1; k >= 0; k--) { // backward recursion
norm = INF;
for (int j = 0; j < S; j++) {
minm = INF;
for (int i = 0; i < I; i++) {
int i0 = j * I + i;
mm = beta[(k + 1) * S + NS[i0]] + priori[k * I + i] +
prioro[k * O + OS[i0]];
minm = (*p2mymin)(minm, mm);
}
beta[k * S + j] = minm;
if (minm < norm)
norm = minm;
}
for (int j = 0; j < S; j++)
beta[k * S + j] -= norm; // normalize total metrics so they do not explode
}
if (POSTI && POSTO) {
for (int k = 0; k < K; k++) { // input combining
norm = INF;
for (int i = 0; i < I; i++) {
minm = INF;
for (int j = 0; j < S; j++) {
mm = alpha[k * S + j] + prioro[k * O + OS[j * I + i]] +
beta[(k + 1) * S + NS[j * I + i]];
minm = (*p2mymin)(minm, mm);
}
post[k * (I + O) + i] = minm;
if (minm < norm)
norm = minm;
}
for (int i = 0; i < I; i++)
post[k * (I + O) + i] -= norm; // normalize metrics
}
for (int k = 0; k < K; k++) { // output combining
norm = INF;
for (int n = 0; n < O; n++) {
minm = INF;
for (int j = 0; j < S; j++) {
for (int i = 0; i < I; i++) {
mm = (n == OS[j * I + i] ? alpha[k * S + j] + priori[k * I + i] +
beta[(k + 1) * S + NS[j * I + i]]
: INF);
minm = (*p2mymin)(minm, mm);
}
}
post[k * (I + O) + I + n] = minm;
if (minm < norm)
norm = minm;
}
for (int n = 0; n < O; n++)
post[k * (I + O) + I + n] -= norm; // normalize metrics
}
} else if (POSTI) {
for (int k = 0; k < K; k++) { // input combining
norm = INF;
for (int i = 0; i < I; i++) {
minm = INF;
for (int j = 0; j < S; j++) {
mm = alpha[k * S + j] + prioro[k * O + OS[j * I + i]] +
beta[(k + 1) * S + NS[j * I + i]];
minm = (*p2mymin)(minm, mm);
}
post[k * I + i] = minm;
if (minm < norm)
norm = minm;
}
for (int i = 0; i < I; i++)
post[k * I + i] -= norm; // normalize metrics
}
} else if (POSTO) {
for (int k = 0; k < K; k++) { // output combining
norm = INF;
for (int n = 0; n < O; n++) {
minm = INF;
for (int j = 0; j < S; j++) {
for (int i = 0; i < I; i++) {
mm = (n == OS[j * I + i] ? alpha[k * S + j] + priori[k * I + i] +
beta[(k + 1) * S + NS[j * I + i]]
: INF);
minm = (*p2mymin)(minm, mm);
}
}
post[k * O + n] = minm;
if (minm < norm)
norm = minm;
}
for (int n = 0; n < O; n++)
post[k * O + n] -= norm; // normalize metrics
}
} else
throw std::runtime_error("Not both POSTI and POSTO can be false.");
}
//---------
template void siso_algorithm_combined<short>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
bool POSTI,
bool POSTO,
float (*p2mymin)(float, float),
int D,
const std::vector<short>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* priori,
const short* observations,
float* post);
template void siso_algorithm_combined<int>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
bool POSTI,
bool POSTO,
float (*p2mymin)(float, float),
int D,
const std::vector<int>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* priori,
const int* observations,
float* post);
template void siso_algorithm_combined<float>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
bool POSTI,
bool POSTO,
float (*p2mymin)(float, float),
int D,
const std::vector<float>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* priori,
const float* observations,
float* post);
template void siso_algorithm_combined<gr_complex>(int I,
int S,
int O,
const std::vector<int>& NS,
const std::vector<int>& OS,
const std::vector<std::vector<int>>& PS,
const std::vector<std::vector<int>>& PI,
int K,
int S0,
int SK,
bool POSTI,
bool POSTO,
float (*p2mymin)(float, float),
int D,
const std::vector<gr_complex>& TABLE,
digital::trellis_metric_type_t TYPE,
const float* priori,
const gr_complex* observations,
float* post);
//=========================================================
template <class Ti, class To>
void sccc_decoder_combined(const fsm& FSMo,
int STo0,
int SToK,
const fsm& FSMi,
int STi0,
int STiK,
const interleaver& INTERLEAVER,
int blocklength,
int iterations,
float (*p2mymin)(float, float),
int D,
const std::vector<Ti>& TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const Ti* observations,
To* data)
{
// allocate space for priori, prioro and posti of inner FSM
std::vector<float> ipriori(blocklength * FSMi.I(), 0.0);
std::vector<float> iprioro(blocklength * FSMi.O());
std::vector<float> iposti(blocklength * FSMi.I());
// allocate space for priori, prioro and posto of outer FSM
std::vector<float> opriori(blocklength * FSMo.I(), 0.0);
std::vector<float> oprioro(blocklength * FSMo.O());
std::vector<float> oposti(blocklength * FSMo.I());
std::vector<float> oposto(blocklength * FSMo.O());
// turn observations to neg-log-priors
for (int k = 0; k < blocklength; k++) {
calc_metric(FSMi.O(),
D,
TABLE,
&(observations[k * D]),
&(iprioro[k * FSMi.O()]),
METRIC_TYPE);
iprioro[k * FSMi.O()] *= scaling;
}
for (int rep = 0; rep < iterations; rep++) {
// run inner SISO
siso_algorithm(FSMi.I(),
FSMi.S(),
FSMi.O(),
FSMi.NS(),
FSMi.OS(),
FSMi.PS(),
FSMi.PI(),
blocklength,
STi0,
STiK,
true,
false,
p2mymin,
&(ipriori[0]),
&(iprioro[0]),
&(iposti[0]));
// interleave soft info inner -> outer
for (int k = 0; k < blocklength; k++) {
int ki = INTERLEAVER.deinterleaver_indices()[k];
// for(int i=0;i<FSMi.I();i++) {
// oprioro[k*FSMi.I()+i]=iposti[ki*FSMi.I()+i];
//}
memcpy(&(oprioro[k * FSMi.I()]),
&(iposti[ki * FSMi.I()]),
FSMi.I() * sizeof(float));
}
// run outer SISO
if (rep < iterations - 1) { // do not produce posti
siso_algorithm(FSMo.I(),
FSMo.S(),
FSMo.O(),
FSMo.NS(),
FSMo.OS(),
FSMo.PS(),
FSMo.PI(),
blocklength,
STo0,
SToK,
false,
true,
p2mymin,
&(opriori[0]),
&(oprioro[0]),
&(oposto[0]));
// interleave soft info outer --> inner
for (int k = 0; k < blocklength; k++) {
int ki = INTERLEAVER.deinterleaver_indices()[k];
// for(int i=0;i<FSMi.I();i++) {
// ipriori[ki*FSMi.I()+i]=oposto[k*FSMi.I()+i];
//}
memcpy(&(ipriori[ki * FSMi.I()]),
&(oposto[k * FSMi.I()]),
FSMi.I() * sizeof(float));
}
} else // produce posti but not posto
siso_algorithm(FSMo.I(),
FSMo.S(),
FSMo.O(),
FSMo.NS(),
FSMo.OS(),
FSMo.PS(),
FSMo.PI(),
blocklength,
STo0,
SToK,
true,
false,