📄 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 */intgen_met(int mettab[2][256], /* Metric table, [sent sym][rx symbol] */int amp, /* Signal amplitude, units */double esn0, /* Es/N0 ratio in dB */double bias, /* Metric bias; 0 for viterbi, rate for sequential */int scale /* Scale factor */){ double noise; double n; int s,bit; double metrics[2][256]; double p0,p1; /* Es/N0 as power ratio */ esn0 = pow(10.,esn0/10); noise = 0.5/esn0; /* only half the noise for BPSK */ noise = sqrt(noise); /* noise/signal Voltage ratio */ /* 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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