📄 metrics.c
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/* Generate metric tables for a soft-decision convolutional decoder
* assuming gaussian noise on a PSK channel.
*
* Works from "first principles" by evaluating the normal probability
* function and then computing the log-likelihood function
* for every possible received symbol value
*
* Copyright 1995 Phil Karn, KA9Q
*/
/* Symbols are offset-binary, with 128 corresponding to an erased (no
* information) symbol
*/
#define OFFSET 128
#include <stdlib.h>
#include <math.h>
/* Normal function integrated from -Inf to x. Range: 0-1 */
#define normal(x) (0.5 + 0.5*erf((x)/M_SQRT2))
/* Logarithm base 2 */
#define log2(x) (log(x)*M_LOG2E)
/* Generate log-likelihood metrics for 8-bit soft quantized channel
* assuming AWGN and BPSK
*/
int
gen_met(
int mettab[2][256], /* Metric table, [sent sym][rx symbol] */
int amp, /* Signal amplitude, units */
double noise, /* Relative noise voltage */
double bias, /* Metric bias; 0 for viterbi, rate for sequential */
int scale /* Scale factor */
){
double n;
int s,bit;
double metrics[2][256];
double p0,p1;
/* Zero is a special value, since this sample includes all
* lower samples that were clipped to this value, i.e., it
* takes the whole lower tail of the curve
*/
p1 = normal(((0-OFFSET+0.5)/amp - 1)/noise); /* P(s|1) */
/* Prob of this value occurring for a 0-bit */ /* P(s|0) */
p0 = normal(((0-OFFSET+0.5)/amp + 1)/noise);
metrics[0][0] = log2(2*p0/(p1+p0)) - bias;
metrics[1][0] = log2(2*p1/(p1+p0)) - bias;
for(s=1;s<255;s++){
/* P(s|1), prob of receiving s given 1 transmitted */
p1 = normal(((s-OFFSET+0.5)/amp - 1)/noise) -
normal(((s-OFFSET-0.5)/amp - 1)/noise);
/* P(s|0), prob of receiving s given 0 transmitted */
p0 = normal(((s-OFFSET+0.5)/amp + 1)/noise) -
normal(((s-OFFSET-0.5)/amp + 1)/noise);
#ifdef notdef
printf("P(%d|1) = %lg, P(%d|0) = %lg\n",s,p1,s,p0);
#endif
metrics[0][s] = log2(2*p0/(p1+p0)) - bias;
metrics[1][s] = log2(2*p1/(p1+p0)) - bias;
}
/* 255 is also a special value */
/* P(s|1) */
p1 = 1 - normal(((255-OFFSET-0.5)/amp - 1)/noise);
/* P(s|0) */
p0 = 1 - normal(((255-OFFSET-0.5)/amp + 1)/noise);
metrics[0][255] = log2(2*p0/(p1+p0)) - bias;
metrics[1][255] = log2(2*p1/(p1+p0)) - bias;
#ifdef notdef
/* The probability of a raw symbol error is the probability
* that a 1-bit would be received as a sample with value
* 0-128. This is the offset normal curve integrated from -Inf to 0.
*/
printf("symbol Pe = %lg\n",normal(-1/noise));
#endif
for(bit=0;bit<2;bit++){
for(s=0;s<256;s++){
/* Scale and round to nearest integer */
mettab[bit][s] = floor(metrics[bit][s] * scale + 0.5);
#ifdef notdef
printf("metrics[%d][%d] = %lg, mettab = %d\n",
bit,s,metrics[bit][s],mettab[bit][s]);
#endif
}
}
}
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