other_functions.c

禁忌搜索算法的源代码

#include "turbo_code_Log_MAP.h"
#include "other_functions.h"

/*---------------------------------------------------------------
FUNCTION: 
	void gen_source(int *data, int length)
	
DESCRIPTION:
	This function generate the source bits for simulation.

PARAMETERS:
	INPUT:
		length - Length of needed data.
	OUTPUT:
		data - Contains pointer to source data sequence.

RETURN VALUE:
	None
---------------------------------------------------------------*/
void gen_source(int *data, int length)
{
	double temp;
	int i;

	for (i=0; i<length; i++)
	{
		//temp = (double)rand()/RAND_MAX;
		temp = random_turbo();
		if (temp <= 0.5)
		{
			*(data+i) = 0;
		}
		else 
		{
			*(data+i) = 1;
		}
	}

}


/*---------------------------------------------------------------
FUNCTION: 
	void AWGN(int *send, double *r, double sigma, int totallength)
	
DESCRIPTION:
	This function simulate a AWGN channel.

PARAMETERS:
	INPUT:
		send - Input bit sequence need to add noise.
		sigma - Standard deviation of AWGN noise
		totallength - Length of "send".
	OUTPUT:
		r - Contains pointer to the data sequence added with gaussian white noise.

RETURN VALUE:
	None
---------------------------------------------------------------*/
void AWGN(float *send, float *r, float sigma, int totallength)
{
	int i;
	double *noise = (double *)malloc(sizeof(double)*totallength);
	double seed =  3.0 - (double)((rand() & RAND_MAX)/(double)RAND_MAX)/10e6;
	mgrns(0,sigma,seed,totallength,noise);
	for(i=0; i<totallength; i++)
	{
		*(r+i) = (float)( *(send+i) + *(noise+i) );
	}
	free(noise);
}

/*
* 函数介绍：产生长度为n的高斯随机序列
* 输入参数：mean：均值
            sigma：标准差
			seed：一个随机种子
* 输出参数：a：长度为n的高斯随机序列
* 返回值：  返回一个trellis结构
*/
void mgrns(double mean,double sigma,double seed,int n,double *a)
{ int i,k,m;
    double s,w,v,t;
    s=65536.0; w=2053.0; v=13849.0;
    for (k=0; k<=n-1; k++)
	{
		t=0.0;
		for (i=1; i<=12; i++)
        { 
			seed=seed*w+v; m=(int)(seed/s);
            seed=seed-m*s; t=t+(seed)/s;
        }/*按照中心极限定理产生服从高斯分布的随机数*/
        *(a+k)=mean+sigma*(t-6.0);
    }
    return;
}