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📄 noise.c

📁 ofdm的完整系统模型,包含信道参数,多径模型,doppler频移等都可以自由修改!是您做仿真的有力帮助.c语言运行速度快!
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	sgenrand(seedv, mtNew);  /* Initialize with system seed */

	for (i = 1; i < 624 ; i += 2) { /* Alter every other state with new seed */
	    mtNew[i] = ul_seed & 0xffff0000;
	    ul_seed = 69069 * ul_seed + 1;
	    mtNew[i] |= (ul_seed & 0xffff0000) >> 16;
	    ul_seed = 69069 * ul_seed + 1;
	}
	
    }
    return mtNew;
}

/*
 * FUNCTION: double genUDN(ulp_mt)
 * PURPOSE:
 *
 *  Generates uniformly distributed noise
 *  ranging from [0, 1). lp_mt is a ULong
 *  pointer returned from genRandInit.
 *
 * DESCRIPTION:
 * RETURN VALUE:
 * INCLUDE FILES NECESSARY:
 * PROBLEMS/SUGGESTIONS:
 * GLOBALS/SIDE EFFECTS:
 */
double genUDN(ulp_mt)
ULong	*ulp_mt;
{
    return genrand(ulp_mt);
}



/*
 * FUNCTION: double genWGN(ulp_mt)
 * PURPOSE:
 *
 *   Generates white Gaussian noise. lp_mt
 *   is a ULong pointer returned from genRandInit.
 *
 * DESCRIPTION:
 * RETURN VALUE:
 * INCLUDE FILES NECESSARY:
 * PROBLEMS/SUGGESTIONS:
 * GLOBALS/SIDE EFFECTS:
 */
double genWGN(ulp_mt)		
ULong *ulp_mt;
{
    static double nextVal = 0.0;
    static int useNext = 0;

    if (useNext) {
	useNext = 0;
	return nextVal;
    }
    else {
	double r, s, c;
	do {
	    s = 2.0*genUDN(ulp_mt) - 1.0;
	    c = 2.0*genUDN(ulp_mt) - 1.0;
	    r = s*s + c*c;
	} while (r >= 1.0);
	r = sqrt(-2.0*log(r) / r);

	nextVal = c * r;
	useNext = 1;
	return (s * r);
    }
}



/*
 * FUNCTION: double genRandBit(ulp_mt, d_prob_zero)
 * PURPOSE:
 *
 *   Returns a value equal to 0 or 1.  ulp_mt
 *   is a ULong pointer returned by genRandInit.
 *
 * DESCRIPTION:
 * RETURN VALUE:
 * INCLUDE FILES NECESSARY:
 * PROBLEMS/SUGGESTIONS:
 * GLOBALS/SIDE EFFECTS:
 */
double genRandBit(ulp_mt, d_prob_zero)
ULong *ulp_mt;
double d_prob_zero;
{
    return (genUDN(ulp_mt) > d_prob_zero) ? 1.0 : 0.0;
}




/*
 * FUNCTION: double genEXP(ulp_mt)
 * PURPOSE:
 *
 *	Generates an exponentially distributed Random variable.
 *
 * DESCRIPTION:
 *
 *	Returns an exponentially distributed, positive, random deviate
 *	of unit mean, using genUDN(ulp_mt) as the source of
 *	uniform deviates.
 *	This function was retrieved from "Numerical Recipies in C"
 *	by William Press et. al.
 *
 * RETURN VALUE:
 * INCLUDE FILES NECESSARY:
 * PROBLEMS/SUGGESTIONS:
 * GLOBALS/SIDE EFFECTS:
 */
double genEXP(ulp_mt)
ULong *ulp_mt;
{
	double	x;
/*
 *	Returns an exponentially distributed, positive, random 
 *	deviate of unit mean, using noiseUDN(lp_seed) as the 
 *	source of uniform deviates.
 */
	x = genUDN(ulp_mt);
	if (x == 0.0) x = genUDN(ulp_mt);
	
	return -log(x);
}


/*
 * FUNCTION: double genPOISS(ulp_mt, d_mean)
 * PURPOSE:
 *
 *	Function for Poisson distribution
 *
 * DESCRIPTION:
 *
 *	Returns as a floating point number an integer
 *	value that is a random deviate drawn from a
 *	poisson distribution of mean xm, using a source
 *	of uniform random deviates.
 *	This function was retrieved from Chapter 7 of
 *	the "Numerical Recipies in C" by Press et. al.
 *
 * RETURN VALUE:
 * INCLUDE FILES NECESSARY:
 * PROBLEMS/SUGGESTIONS:
 * GLOBALS/SIDE EFFECTS:
 */
double genPOISS(ulp_mt, d_xm)
ULong *ulp_mt;
double	d_xm;
{
    static double	sq, alxm, g;
    static double	oldm = -1.0;
    double		em, t, y;

    if (d_xm < 12.0) {
	if (d_xm != oldm) {
	    oldm = d_xm;
	    g = exp(-d_xm);
	}
	em = -1;
	t = 1.0;
	do {
	    em += 1.0;
	    t *= genUDN(ulp_mt);
	} while (t > g);
    }
    else {
	if (d_xm != oldm) {
	    oldm = d_xm;
	    sq = sqrt(2.0 * d_xm);
	    alxm = log(d_xm);
	    g = d_xm * alxm - gammln(d_xm + 1.0);
	}
	do {
	    do {
		y = tan(PI * genUDN(ulp_mt));
		em = sq * y + d_xm;
	    } while (em < 0.0);
	    em = floor(em);
	    t = 0.9 * (1.0 + y*y) * exp(em * alxm - gammln(em + 1.0) - g);
	} while (genUDN(ulp_mt) > t);
    }

    return em;
}
/*
 * A slightly altered version of mt19937 to handle passing
 * the random number generator state as an argument to allow
 * for multiple generator instances.  Below is the original
 * comment for the mt19937-2.c file but this is slightly modified
 * to handle multiple random generator states.  The original
 * file is provided at mt19937-2.c
 *
 */
/* A C-program for MT19937: Real number version (1999/10/28)    */
/*   genrand() generates one pseudorandom real number (double)  */
/* which is uniformly distributed on [0,1]-interval, for each   */
/* call. sgenrand(seed) sets initial values to the working area */
/* of 624 words. Before genrand(), sgenrand(seed) must be       */
/* called once. (seed is any 32-bit integer.)                   */
/* Integer generator is obtained by modifying two lines.        */
/*   Coded by Takuji Nishimura, considering the suggestions by  */
/* Topher Cooper and Marc Rieffel in July-Aug. 1997.            */

/* This library is free software under the Artistic license:       */
/* see the file COPYING distributed together with this code.       */
/* For the verification of the code, its output sequence file      */
/* mt19937-1.out is attached (2001/4/2)                           */

/* Copyright (C) 1997, 1999 Makoto Matsumoto and Takuji Nishimura. */
/* Any feedback is very welcome. For any question, comments,       */
/* see http://www.math.keio.ac.jp/matumoto/emt.html or email       */
/* matumoto@math.keio.ac.jp                                        */

/* REFERENCE                                                       */
/* M. Matsumoto and T. Nishimura,                                  */
/* "Mersenne Twister: A 623-Dimensionally Equidistributed Uniform  */
/* Pseudo-Random Number Generator",                                */
/* ACM Transactions on Modeling and Computer Simulation,           */
/* Vol. 8, No. 1, January 1998, pp 3--30.                          */

#include<stdio.h>

/* Period parameters */  
#define N 624
#define M 397
#define MATRIX_A 0x9908b0df   /* constant vector a */
#define UPPER_MASK 0x80000000 /* most significant w-r bits */
#define LOWER_MASK 0x7fffffff /* least significant r bits */

/* Tempering parameters */   
#define TEMPERING_MASK_B 0x9d2c5680
#define TEMPERING_MASK_C 0xefc60000
#define TEMPERING_SHIFT_U(y)  (y >> 11)
#define TEMPERING_SHIFT_S(y)  (y << 7)
#define TEMPERING_SHIFT_T(y)  (y << 15)
#define TEMPERING_SHIFT_L(y)  (y >> 18)

/*
 * Not used
static unsigned long mt[N+1]; *//* the array for the state vector  */
/*
 * Not used
static int mti=N+1; *//* mti==N+1 means mt[N] is not initialized */

/* Initializing the array with a seed */
static void sgenrand(seed, gen_array)
unsigned long seed;
ULong *gen_array;
{
    int i;

    for (i=0;i<N;i++) {
	gen_array[i] = seed & 0xffff0000;
	seed = 69069 * seed + 1;
	gen_array[i] |= (seed & 0xffff0000) >> 16;
	seed = 69069 * seed + 1;
    }
    gen_array[N] = N;
}

/* Initialization by "sgenrand()" is an example. Theoretically,      */
/* there are 2^19937-1 possible states as an intial state.           */
/* This function allows to choose any of 2^19937-1 ones.             */
/* Essential bits in "seed_array[]" is following 19937 bits:         */
/*  (seed_array[0]&UPPER_MASK), seed_array[1], ..., seed_array[N-1]. */
/* (seed_array[0]&LOWER_MASK) is discarded.                          */ 
/* Theoretically,                                                    */
/*  (seed_array[0]&UPPER_MASK), seed_array[1], ..., seed_array[N-1]  */
/* can take any values except all zeros.                             */
/* Not used */
#if 0
static void
lsgenrand(seed_array)
    unsigned long seed_array[];
    /* the length of seed_array[] must be at least N */
{
    int i;

    for (i=0;i<N;i++) 
      mt[i] = seed_array[i];
    mti=N;
}
#endif

static double /* generating reals */
/* unsigned long */ /* for integer generation */
genrand(gen_array)
unsigned long *gen_array;
{
    unsigned long y;
    static unsigned long mag01[2]={0x0, MATRIX_A};
    long mti = gen_array[N];
    /* mag01[x] = x * MATRIX_A  for x=0,1 */

    if (mti >= N) { /* generate N words at one time */
        int kk;

        if (mti == N+1)   /* if sgenrand() has not been called, */
            sgenrand(4357); /* a default initial seed is used   */

        for (kk=0;kk<N-M;kk++) {
            y = (gen_array[kk]&UPPER_MASK)|(gen_array[kk+1]&LOWER_MASK);
            gen_array[kk] = gen_array[kk+M] ^ (y >> 1) ^ mag01[y & 0x1];
        }
        for (;kk<N-1;kk++) {
            y = (gen_array[kk]&UPPER_MASK)|(gen_array[kk+1]&LOWER_MASK);
            gen_array[kk] = gen_array[kk+(M-N)] ^ (y >> 1) ^ mag01[y & 0x1];
        }
        y = (gen_array[N-1]&UPPER_MASK)|(gen_array[0]&LOWER_MASK);
        gen_array[N-1] = gen_array[M-1] ^ (y >> 1) ^ mag01[y & 0x1];

        mti = 0;
    }
  
    y = gen_array[mti++];
    y ^= TEMPERING_SHIFT_U(y);
    y ^= TEMPERING_SHIFT_S(y) & TEMPERING_MASK_B;
    y ^= TEMPERING_SHIFT_T(y) & TEMPERING_MASK_C;
    y ^= TEMPERING_SHIFT_L(y);

    gen_array[N] = mti;
    return ( (double)y * 2.3283064370807974e-10 ); /* reals */
    /* return y; */ /* for integer generation */
}

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