Multi-user detection in multi-carrier CDMA wireless broadband system using a binary adaptive differential evolution algorithm

Abstract

Multi-Carrier Code Division Multiple Access (MC-CDMA) is an emerging wireless communication technology that incorporates the advantages of Orthogonal Frequency Division Multiplexing (OFDM) into the original Code Division Multiple Access (CDMA) technique. But it suffers from the inherent defect called Multiple Access Interference (MAI) due to inappropriate cross-correlation possessed by the different user codes. To reduce MAI, the multi-user detection (MUD) technique has already been proposed in which MAI is treated as noise. Due to high computational cost incorporated by the optimal MUD detector with increasing number of users, researchers are looking for sub-optimal MUD solutions. This paper proposes a binary adaptive Differential Evolution algorithm with a novel crossover strategy (MBDE_pBX) for multi-user detection in a synchronous MC-CDMA system. Since MUD detection in MC-CDMA systems is a problem in binary domain, a binary encoding rule is introduced which converts a binary domain problem of any number of dimensions into a 4-dimensional continuous domain problem. The simulation results show that this new binary Differential Evolution variant can achieve superior bit error rate (BER) performance within much lower optimum solution detection time outperforming its competitors as well as achieving 99.62% reduction in computational complexity as compared to the MUD scheme using exhaustive search.