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// This example demonstrates the autocorr (auto-correlation) object
// functionality. A random time-domain sequence is generated which
// exhibits time-domain repetitions (auto-correlation properties),
// for example: abcdabcdabcd....abcd. The sequence is pushed through
// the autocorr object, and the results are written to an output file.
// The command-line arguments allow the user to experiment with the
// sequence length, number of sequence repetitions, and properties of
// the auto-correlator, as well as signal-to-noise ratio.
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <getopt.h>
#include <math.h>
#include "liquid.h"
#define OUTPUT_FILENAME "autocorr_cccf_example.m"
// print usage/help message
void usage()
{
printf("autocorr_cccf_example:\n");
printf(" u/h : print usage/help\n");
printf(" m : sequence length, default: 32\n");
printf(" n : number of sequences (repetitions), default: 8\n");
printf(" w : autocorr window length, default: 64\n");
printf(" d : autocorr delay length (multiple of 's'), default: 32\n");
printf(" e : normalize by energy? default: off\n");
printf(" s : SNR, signal-to-noise ratio [dB], default: 20\n");
}
int main(int argc, char*argv[]) {
// options
unsigned int sequence_len = 32; // short sequence length
unsigned int n = 8; // number short sequences (repetition length)
unsigned int window_size = 64; // autocorr window size
unsigned int delay = sequence_len; // autocorr delay (multiple of 's')
int normalize_by_energy = 0; // normalize output by E{x^2}?
float SNRdB=20.0f; // signal-to-noise ratio (dB)
int dopt;
while ((dopt = getopt(argc,argv,"uhm:n:w:d:es:")) != EOF) {
switch (dopt) {
case 'u':
case 'h': usage(); return 0;
case 'm': sequence_len = atof(optarg); break;
case 'n': n = atof(optarg); break;
case 'w': window_size = atof(optarg); break;
case 'd': delay = atof(optarg); break;
case 'e': normalize_by_energy = 1; break;
case 's': SNRdB = atoi(optarg); break;
usage();
return 1;
}
}
// derived values
unsigned int num_samples = sequence_len*(n+2); // pad end w/ zeros
// data arrays
float complex sequence[sequence_len]; // short sequence
float complex x[num_samples]; // autocorr input sequence
float complex rxx[num_samples]; // autocorr output
// generate objects
autocorr_cccf q = autocorr_cccf_create(window_size,delay);
unsigned int i;
// generate random training sequence using QPSK symbols
modemcf mod = modemcf_create(LIQUID_MODEM_QPSK);
for (i=0; i<sequence_len; i++)
modemcf_modulate(mod, rand()%4, &sequence[i]);
modemcf_destroy(mod);
// write training sequence 'n' times, followed by zeros
unsigned int t=0;
for (i=0; i<n; i++) {
// copy sequence
memmove(&x[t], sequence, sequence_len*sizeof(float complex));
t += sequence_len;
}
// pad end with zeros
for (i=t; i<num_samples; i++)
x[i] = 0;
// add noise
float nstd = powf(10.0f, -SNRdB/20.0f);
for (i=0; i<num_samples; i++)
cawgn(&x[i],nstd);
// compute auto-correlation
for (i=0; i<num_samples; i++) {
autocorr_cccf_push(q,x[i]);
autocorr_cccf_execute(q,&rxx[i]);
// normalize by energy
if (normalize_by_energy)
rxx[i] /= autocorr_cccf_get_energy(q);
}
// find peak
float complex rxx_peak = 0;
for (i=0; i<num_samples; i++) {
if (i==0 || cabsf(rxx[i]) > cabsf(rxx_peak))
rxx_peak = rxx[i];
}
printf("peak auto-correlation : %12.8f, angle %12.8f\n", cabsf(rxx_peak),
cargf(rxx_peak));
// destroy allocated objects
autocorr_cccf_destroy(q);
//
// write results to file
//
FILE* fid = fopen(OUTPUT_FILENAME, "w");
fprintf(fid,"%% %s : auto-generated file\n", OUTPUT_FILENAME);
fprintf(fid,"clear all;\n");
fprintf(fid,"close all;\n\n");
fprintf(fid,"num_samples = %u;\n", num_samples);
// write signal to output file
for (i=0; i<num_samples; i++) {
fprintf(fid,"x (%4u) = %12.4e + j*%12.4e;\n", i+1, crealf(x[i] ), cimagf(x[i] ));
fprintf(fid,"rxx(%4u) = %12.4e + j*%12.4e;\n", i+1, crealf(rxx[i]), cimagf(rxx[i]));
}
fprintf(fid,"t=1:num_samples;\n");
fprintf(fid,"figure('position',[100 100 800 600]);\n");
fprintf(fid,"subplot(2,1,1);\n");
fprintf(fid," plot(t,real(x),t,imag(x));\n");
fprintf(fid," xlabel('sample index');\n");
fprintf(fid," ylabel('received signal');\n");
fprintf(fid," legend('real','imag');\n");
fprintf(fid,"subplot(2,1,2);\n");
fprintf(fid," plot(t,abs(rxx));\n");
fprintf(fid," xlabel('sample index');\n");
fprintf(fid," ylabel('auto-correlation magnitude');\n");
fclose(fid);
printf("data written to %s\n", OUTPUT_FILENAME);
printf("done.\n");
return 0;
}
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