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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
*
* GNU Radio is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3, or (at your option)
* any later version.
*
* GNU Radio is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with GNU Radio; see the file COPYING. If not, write to
* the Free Software Foundation, Inc., 51 Franklin Street,
* Boston, MA 02110-1301, USA.
*/
#include <cstring>
#include <stdexcept>
#include <iostream>
#include <gnuradio/trellis/core_algorithms.h>
#include <gnuradio/trellis/calc_metric.h>
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);
float *metric = new float[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,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];
}
delete [] metric;
}
// Ti = s i f c
// To = b s i
//---------------
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<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<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));
float *prioro = new float[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.");
delete [] prioro;
}
//---------
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.DEINTER()[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.DEINTER()[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,
p2mymin,
&(opriori[0]), &(oprioro[0]), &(oposti[0]));
/*
viterbi_algorithm(FSMo.I(),FSMo.S(),FSMo.O(),
FSMo.NS(), FSMo.OS(), FSMo.PS(), FSMo.PI(),
blocklength,
STo0,SToK,
&(oprioro[0]), data
);
*/
}
// generate hard decisions
for(int k=0;k<blocklength;k++) {
float min=INF;
int mini=0;
for(int i=0;i<FSMo.I();i++) {
if(oposti[k*FSMo.I()+i]<min) {
min=oposti[k*FSMo.I()+i];
mini=i;
}
}
data[k]=(To)mini;
}
}
//-------
template void
sccc_decoder_combined<float,unsigned char>(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<float> &TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const float *observations, unsigned char *data);
template void
sccc_decoder_combined<float,short>(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<float> &TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const float *observations, short *data);
template void
sccc_decoder_combined<float,int>(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<float> &TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const float *observations, int *data);
template void
sccc_decoder_combined<gr_complex,unsigned char>(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<gr_complex> &TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const gr_complex *observations, unsigned char *data
);
template void
sccc_decoder_combined<gr_complex,short>(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<gr_complex> &TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const gr_complex *observations, short *data);
template void
sccc_decoder_combined<gr_complex,int>(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<gr_complex> &TABLE,
digital::trellis_metric_type_t METRIC_TYPE,
float scaling,
const gr_complex *observations, int *data);
//=========================================================
template<class T> void
sccc_decoder(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),
const float *iprioro, T *data)
{
//allocate space for priori, and posti of inner FSM
std::vector<float> ipriori(blocklength*FSMi.I(),0.0);
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());
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.DEINTER()[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.DEINTER()[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,
p2mymin,
&(opriori[0]), &(oprioro[0]), &(oposti[0]));
/*
viterbi_algorithm(FSMo.I(),FSMo.S(),FSMo.O(),
FSMo.NS(), FSMo.OS(), FSMo.PS(), FSMo.PI(),
blocklength,
STo0,SToK,
&(oprioro[0]), data);
*/
}
} // end iterations
// generate hard decisions
for(int k=0;k<blocklength;k++) {
float min=INF;
int mini=0;
for(int i=0;i<FSMo.I();i++) {
if(oposti[k*FSMo.I()+i]<min) {
min=oposti[k*FSMo.I()+i];
mini=i;
}
}
data[k]=(T)mini;
}
}
//-------
template void
sccc_decoder<unsigned char>(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),
const float *iprioro, unsigned char *data);
template void