IDMA.zip_idma

//*******************************************************************************/ // Interleave-Division Multiple-Access (IDMA) // // This is a simulation program for uncoded IDMA system with BPSK modulation // and real channel. For details, please refer to this paper: // W. K. Leung, Lihai Liu and Li Ping, "Interleaving-based multiple access // and iterative chip-by-chip multi-user detection," IEICE Trans. on Commun., // vol. E86-B, pp. 3634-3637, Dec. 2003. // or http://www.ee.cityu.edu.hk/~liping/Research/Journal/idma.pdf // // W.K.Leung // April 2005 //*******************************************************************************/ #include <stdio.h> #include <iostream.h> #include <stdlib.h> #include <math.h> #include "define.h" const int _NUser = NUSER; const int _DataLen = DATALEN; const int _SpreadLen = SPREADLEN; const int _ChipLen = CHIPLEN; const int _ItNum = ITNUM; const int _Block = BLOCK; const int _EbNoNum = EBNONUM; const double _EbNoStart = EBNOSTART; const double _EbNoStep = EBNOSTEP; int Data[NUSER][DATALEN]; int ScrambleRule[NUSER][CHIPLEN]; double Ber[ITNUM]; double H[NUSER], H2[NUSER]; // H2[.] = H[.] * H[.] double Chip[NUSER][CHIPLEN]; double Tx[NUSER][CHIPLEN]; double Rx[CHIPLEN]; double SpreadSeq[SPREADLEN]; double TotalMean[CHIPLEN]; double TotalVar[CHIPLEN]; double Mean[NUSER][CHIPLEN]; double Var[NUSER][CHIPLEN]; double AppLlr[NUSER][DATALEN]; double Ext[NUSER][CHIPLEN]; void Transmitter( ); void Channel( double sigma ); double RandFloat( ); void Receiver( double sigma ); void Initialization( double sigma ); void DeSpreader( int nuser, double *appllr, double *chip ); void EnergyProfile( ); double ErrorCounter( ); void main( ) { int i, j, nuser, tmp, block; double snr, sigma, ebno, error; // Setup the energy level of each user. EnergyProfile( ); // Generate the spreading sequence: {+1, -1, +1, -1, ... }. for( i=0; i<_SpreadLen; i++ ) SpreadSeq[i] = 1 - 2 * ( i % 2 ); // Generate the interleaving index. for( nuser=0; nuser<_NUser; nuser++ ) { for( i=0; i<_ChipLen; i++ ) ScrambleRule[nuser][i] = i; for( i=0; i<_ChipLen-1; i++ ) { j = i + ( rand() * rand() ) % ( _ChipLen - i ); tmp = ScrambleRule[nuser][i]; ScrambleRule[nuser][i] = ScrambleRule[nuser][j]; ScrambleRule[nuser][j] = tmp; } } printf("IDMA: User#=%i, DataLen=%i, SpreadLen=%i and It#=%i\n", _NUser, _DataLen, _SpreadLen, _ItNum ); // The simulation process. for( i=0; i<_EbNoNum; i++ ) { ebno = _EbNoStart + (double) i * _EbNoStep; snr = pow( 10, ebno / 10 ) / (double) _SpreadLen; sigma = sqrt( 0.5 / snr ); error = 0; for( block=1; block<=_Block; block++ ) { Transmitter( ); Channel( sigma ); Receiver( sigma ); error += ErrorCounter( ); printf("Block#=%6i, EbNo=%2.2fdB, BER=%1.3e%c", block, ebno, error / (double) (_NUser * _DataLen * block ), 0x0d ); } printf("\n"); } } void Transmitter( ) { int i, j, m, nuser; double tmp; // Data Generation. for( nuser=0; nuser<_NUser; nuser++ ) for( i=0; i<_DataLen; i++ ) Data[nuser][i] = rand() % 2; // Spreading process. for( nuser=0; nuser<_NUser; nuser++ ) for( m=i=0; i<_DataLen; i++ ) { tmp = 1 - ( 2 * Data[nuser][i] ); for( j=0; j<_SpreadLen; j++ ) Chip[nuser][m++] = tmp * SpreadSeq[j]; } // Interleaving process. for( nuser=0; nuser<_NUser; nuser++ ) for( i=0; i<_ChipLen; i++ ) Tx[nuser][i] = Chip[nuser][ScrambleRule[nuser][i]]; } void Channel( double sigma ) { int i, nuser; for( i=0; i<_ChipLen; i++ ) { // Additive white Gaussian noise. Rx[i] = sigma * sqrt( -2.0 * log( RandFloat() ) ) * cos( 6.283185307 * RandFloat() ); // Multiple access channel and energy scaling. for( nuser=0; nuser<_NUser; nuser++ ) Rx[i] += H[nuser] * Tx[nuser][i]; } } // Serial receiver void Receiver( double sigma ) { int i, j, m, nuser, it; Initialization( sigma ); for( it=0; it<_ItNum; it++ ) for( nuser=0; nuser<_NUser; nuser++ ) { // Produce the LLR values for the de-interleaved chip sequence. for( i=0; i<_ChipLen; i++ ) { TotalMean[i] -= Mean[nuser][i]; TotalVar[i] -= Var[nuser][i]; Chip[nuser][ScrambleRule[nuser][i]] = 2 * H[nuser] * ( Rx[i] - TotalMean[i] ) / TotalVar[i]; } // De-spreading operation. DeSpreader( nuser, &AppLlr[nuser][0], &Chip[nuser][0] ); // Feed the AppLlr to decoder, if there is a FEC codec in the system. // Spreading operation: Produce the extrinsic LLR for each chip for( m=i=0; i<_DataLen; i++ ) for( j=0; j<_SpreadLen; j++, m++ ) Ext[nuser][m] = SpreadSeq[j] * AppLlr[nuser][i] - Chip[nuser][m]; // Update the statistic variable together with the interleaving process. for( i=0; i<_ChipLen; i++ ) { Mean[nuser][i] = H[nuser] * tanh( Ext[nuser][ScrambleRule[nuser][i]] / 2 ); Var[nuser][i] = H2[nuser] - Mean[nuser][i] * Mean[nuser][i]; TotalMean[i] += Mean[nuser][i]; TotalVar[i] += Var[nuser][i]; } } } /* // Parallel receiver void Receiver( double sigma ) { int i, j, m, nuser, it; double s2 = sigma * sigma; Initialization( sigma ); for( it=0; it<_ItNum; it++ ) { for( nuser=0; nuser<_NUser; nuser++ ) { // Produce the LLR values for the de-interleaved chip sequence. for( i=0; i<_ChipLen; i++ ) Chip[nuser][ScrambleRule[nuser][i]] = 2 * H[nuser] * ( Rx[i] - ( TotalMean[i] - Mean[nuser][i] ) ) / ( TotalVar[i] - Var[nuser][i] ); // De-spreading operation. DeSpreader( nuser, &AppLlr[nuser][0], &Chip[nuser][0] ); // Feed the AppLlr to decoder, if there is a FEC codec in the system. // Spreading operation: Produce the extrinsic LLR for each chip for( m=i=0; i<_DataLen; i++ ) for( j=0; j<_SpreadLen; j++, m++ ) Ext[nuser][m] = SpreadSeq[j] * AppLlr[nuser][i] - Chip[nuser][m]; } // Update the statistic variable together with the interleaving process. for( i=0; i<_ChipLen; i++ ) { TotalMean[i] = 0; TotalVar[i] = s2; } for( nuser=0; nuser<_NUser; nuser++ ) for( i=0; i<_ChipLen; i++ ) { Mean[nuser][i] = H[nuser] * tanh( Ext[nuser][ScrambleRule[nuser][i]] / 2 ); Var[nuser][i] = H2[nuser] - Mean[nuser][i] * Mean[nuser][i]; TotalMean[i] += Mean[nuser][i]; TotalVar[i] += Var[nuser][i]; } } } */ void DeSpreader( int nuser, double *appllr, double *chip ) { int i, j, m; for( m=i=0; i<_DataLen; i++ ) { appllr[i] = SpreadSeq[0] * chip[m++]; for( j=1; j<_SpreadLen; j++ ) appllr[i] += SpreadSeq[j] * chip[m++]; } } double ErrorCounter( ) { int i, nuser; double e = 0; for( nuser=0; nuser<_NUser; nuser++ ) for( i=0; i<_DataLen; i++ ) e += ( Data[nuser][i] != STEP( AppLlr[nuser][i] ) ); return e; } void Initialization( double sigma ) { int i, nuser; double s2 = sigma * sigma; for( i=0; i<_ChipLen; i++ ) { TotalMean[i] = 0; TotalVar[i] = s2; } for( nuser=0; nuser<_NUser; nuser++ ) for( i=0; i<_ChipLen; i++ ) { Mean[nuser][i] = 0; Var[nuser][i] = H2[nuser]; TotalVar[i] += H2[nuser]; } } double RandFloat( ) { // Generate a uniform distributed varable in the interval (0,1). return (double) ( rand() + 1 ) / (double) ( RAND_MAX + 2 ); }