A novel multiuser detection based on honey bees mating optimisation and tabu search algorithm for SDMA-OFDM systems

Abstract

In the wireless communication systems, the classic Multi-User Detection (MUD) techniques such as the Minimum Mean Square Error (MMSE) detector have some limitations and imperfections due to Multi-Access Interference (MAI) especially in overloaded scenarios when the number of users is more than the number of receiving antennas. The optimal Maximum Likelihood (ML) detector gives an excellent result to estimate the transmitted data but suffers from a computational complexity that grows exponentially with the number of users. In this paper, we propose a new metaheuristic approach for multiuser detection based on Honey Bees Mating Optimisation (HBMO) hybridised with Tabu Search (TS) for an uplink Space Division Multiple Access-Orthogonal Frequency Division Multiplexing (SDMA-OFDM) system in a flat Rayleigh fading channel. Indeed, the HBMO algorithm provides a good estimation for TS while exploring the largest regions, while the TS algorithm uses this estimation to find the best solution of the problem. The simulation results show that the proposed algorithm HBMO-TS-MUD provides the best trade-off between performance and computational complexity comparing to the conventional detector and the other MUD detectors proposed as Genetic Algorithm hybridised with the Tabu Search (GA-TS).