Multiuser detection using the Particle Swarm Optimization Algorithm

Particle Swarm Optimization (PSO) algorithm is an efficient stochastic global optimization technique making use of a particle population, where each particle represents a solution to the problem being optimized. PSO find optimal regions of complex search spaces through the interaction of individuals in a population of particles. In this paper, PSO algorithm is applied to solve the Multiuser Detection (MUD) problems in Direct Sequence Code Division Multiple Access (DS-CDMA) system, which reduces the computational complexity by providing faster convergence. The algorithm can be implemented with ease, and provide a more robust algorithm and better near-far resistance with parallel processing. 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 Genetic Algorithm (GA) or Evolution Programming (EP) in terms of bit-error-rate and convergence rate.