Multiuser detection using the particle swarm optimization algorithm

Genetic algorithm (GA) has proven to be a useful method of optimization for multidimensional engineering problems. A new method named particle swarm optimization (PSO) has been proposed by Kennedy and Eberhart and it is similar in some ways to GA or evolutionary programming (EP). In this paper, we apply PSO to solve the multiuser detection (MUD) problems in the DS-CDMA system, which reduces the computational complexity by providing faster convergence. The simulation results show that the proposed detections benefit greatly from the PSO and have significant performance improvements over conventional detector (CD) and previous multiuser detectors based on GA and EP in terms of bit-error-rate and convergence rate.