Multiuser Detection For DS-CDMA Systems Using Honeybees Mating Optimization Algorithm

The future wireless mobile communication systems will be required to support high-speed transmission rate and high quality of service. Direct sequence code division multiple access (DS-CDMA) is an important scheme for high-rate wireless communication. The capacity of DS-CDMA can be impaired by two problems; near-far effect and multiple-access interference (MAI). The use of conventional-matched filter detector for multiple users in DS-CDMA fails to combat any of these problems. The performance degradation caused by MAI can be overcome using multiuser detection (MUD). The use of maximum likelihood (ML) sequence estimation detector provides excellent results, but involves high computational complexity. In this paper, we propose a new meta-heuristic approach for MUD using honeybees mating optimization (HBMO) algorithm to detect the user bits based on the ML decision rule for DS-CDMA systems in additive white-Gaussian noise and flat Rayleigh fading channels. In order to improve the solutions generated by the HBMO, a second meta-heuristic method simulated annealing is used. By computer simulations, the bit error rate performance and the complexity curves show that the proposed HBMO-SA MUD is capable of outperforming the other conventional detectors and genetic algorithm detector.