// qracodes.c
// Q-ary RA codes encoding/decoding functions
//
// (c) 2016 - Nico Palermo, IV3NWV - Microtelecom Srl, Italy
// ------------------------------------------------------------------------------
// This file is part of the qracodes project, a Forward Error Control
// encoding/decoding package based on Q-ary RA (Repeat and Accumulate) LDPC codes.
//
// qracodes 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 of the License, or
// (at your option) any later version.
// qracodes 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 qracodes source distribution.
// If not, see .
#include
#include
#include "npfwht.h"
#include "pdmath.h"
#include "qracodes.h"
#define QRA_DEBUG
int qra_encode(const qracode *pcode, int *y, const int *x)
{
int k,j,kk,jj;
int t, chk = 0;
const int K = pcode->K;
const int M = pcode->M;
const int NC= pcode->NC;
const int a = pcode->a;
const int *acc_input_idx = pcode->acc_input_idx;
const int *acc_input_wlog = pcode->acc_input_wlog;
const int *gflog = pcode->gflog;
const int *gfexp = pcode->gfexp;
// copy the systematic symbols to destination
memcpy(y,x,K*sizeof(int));
y = y+K; // point to check symbols
// compute the code check symbols as a weighted accumulation of a permutated
// sequence of the (repeated) systematic input symbols:
// chk(k+1) = x(idx(k))*alfa^(logw(k)) + chk(k)
// (all operations performed over GF(M))
if (a==1) { // grouping factor = 1
for (k=0;k 1
for (k=0;k80.f) // avoid floating point exp() overflows
v=80.f;
src[nitems] = (float)exp(v);
}
}
void qra_mfskbesselmetric(float *pix, const float *rsq, const int m, const int N, float EsNoMetric)
{
// Computes the codeword symbols intrinsic probabilities
// given the square of the received input amplitudes.
// The input vector rqs must be a linear array of size M*N, where M=2^m,
// containing the squared amplitudes (rp*rp+rq*rq) of the input samples
// First symbol amplitudes should be stored in the first M positions,
// second symbol amplitudes stored at positions [M ... 2*M-1], and so on.
// Output vector is the intrinsic symbol metric (the probability distribution)
// assuming that symbols are transmitted using a M-FSK modulation
// and incoherent demodulation.
// As the input Es/No is generally unknown (as it cannot be exstimated accurately
// when the codeword length is few tens symbols) but an exact metric requires it
// we simply fix it to a predefined EsNoMetric value so that the metric is what
// expected at that specific value.
// The metric computed in this way is optimal only at this predefined Es/No value,
// nevertheless it is usually better than a generic parameter-free metric which
// makes no assumptions on the input Es/No.
int k;
float rsum = 0.f;
float sigmaest, cmetric;
const int M = 1<M;
const int qra_m = pcode->m;
const int qra_V = pcode->V;
const int qra_MAXVDEG = pcode->MAXVDEG;
const int *qra_vdeg = pcode->vdeg;
const int qra_C = pcode->C;
const int qra_MAXCDEG = pcode->MAXCDEG;
const int *qra_cdeg = pcode->cdeg;
const int *qra_v2cmidx = pcode->v2cmidx;
const int *qra_c2vmidx = pcode->c2vmidx;
const int *qra_pmat = pcode->gfpmat;
const int *qra_msgw = pcode->msgw;
// float msgout[qra_M]; // buffer to store temporary results
float msgout[QRACODE_MAX_M]; // we use a fixed size in order to avoid mallocs
float totex; // total extrinsic information
int nit; // current iteration
int nv; // current variable
int nc; // current check
int k,kk; // loop indexes
int ndeg; // current node degree
int msgbase; // current offset in the table of msg indexes
int imsg; // current message index
int wmsg; // current message weight
int rc = -1; // rc>=0 extrinsic converged to 1 at iteration rc (rc=0..maxiter-1)
// rc=-1 no convergence in the given number of iterations
// rc=-2 error in the code tables (code checks degrees must be >1)
// rc=-3 M is larger than QRACODE_MAX_M
if (qra_M>QRACODE_MAX_M)
return -3;
// message initialization -------------------------------------------------------
// init c->v variable intrinsic msgs
pd_init(C2VMSG(0),pix,qra_M*qra_V);
// init the v->c messages directed to code factors (k=1..ndeg) with the intrinsic info
for (nv=0;nvc
for (k=1;kv step -----------------------------------------------------
// Computes messages from code checks to code variables.
// As the first qra_V checks are associated with intrinsic information
// (the code tables have been constructed in this way)
// we need to do this step only for code checks in the range [qra_V..qra_C)
// The convolutions of probability distributions over the alphabet of a finite field GF(qra_M)
// are performed with a fast convolution algorithm over the given field.
//
// I.e. given the code check x1+x2+x3 = 0 (with x1,x2,x3 in GF(2^m))
// and given Prob(x2) and Prob(x3), we have that:
// Prob(x1=X1) = Prob((x2+x3)=X1) = sum((Prob(x2=X2)*Prob(x3=(X1+X2))) for all the X2s in the field
// This translates to Prob(x1) = IWHT(WHT(Prob(x2))*WHT(Prob(x3)))
// where WHT and IWHT are the direct and inverse Walsh-Hadamard transforms of the argument.
// Note that the WHT and the IWHF differs only by a multiplicative coefficent and since in this step
// we don't need that the output distribution is normalized we use the relationship
// Prob(x1) =(proportional to) WH(WH(Prob(x2))*WH(Prob(x3)))
// In general given the check code x1+x2+x3+..+xm = 0
// the output distribution of a variable given the distributions of the other m-1 variables
// is the inverse WHT of the product of the WHTs of the distribution of the other m-1 variables
// The complexity of this algorithm scales with M*log2(M) instead of the M^2 complexity of
// the brute force approach (M=size of the alphabet)
for (nc=qra_V;nc1)
return -2; // bad code tables
msgbase = nc*qra_MAXCDEG; // base to msg index row for the current node
// transforms inputs in the Walsh-Hadamard "frequency" domain
// v->c -> fwht(v->c)
for (k=0;kv = prod(fwht(v->c))
// TODO: we assume that checks degrees are not larger than three but
// if they are larger the products can be computed more efficiently
for (kk=0;kkc steps when multipling
// small fp numbers
msgout[0]+=1E-7f; // TODO: define the bias accordingly to the field size
np_fwht(qra_m,msgout,msgout);
// inverse weight and output
imsg = qra_c2vmidx[msgbase+k]; // current output msg index
wmsg = qra_msgw[imsg]; // current msg weight
if (wmsg==0)
pd_init(C2VMSG(imsg),msgout,qra_M);
else
// output p(alfa^(-w)*x)
pd_bwdperm(C2VMSG(imsg),msgout, MSGPERM(wmsg), qra_M);
} // for (k=0;kc step -----------------------------------------------------
for (nv=0;nvc msg = prod(c->v)
// TODO: factor factors to reduce the number of computations for high degree nodes
for (kk=0;kkc are null
// normalize output to a probability distribution
if (pd_norm(msgout,qra_m)<=0) {
// dump msgin;
printf("warning: v->c pd with invalid norm. nit=%d nv=%d k=%d\n",nit,nv,k);
for (kk=0;kk(1.*(qra_V)-0.01)) {
// the total maximum extrinsic information of each symbol in the codeword
// is very close to one. This means that we have reached the (1,1) point in the
// code EXIT chart(s) and we have successfully decoded the input.
rc = nit;
break; // remove the break to evaluate the decoder speed performance as a function of the max iterations number)
}
} // for (nit=0;nitM;
const int qra_m = pcode->m;
const int qra_K = pcode->K;
int k;
for (k=0;k