Particle Swarm and Quantum Particle Swarm Optimization Applied to DS/CDMA Multiuser Detection in Flat Rayleigh Channels

Abstract

The particle swarm and quantum particle swarm optimization (PSO and QPSO) techniques applied to Direct Sequence/Code Division Multiple Access systems (DS/CDMA) with multiuser detection (MuD) are analyzed, evaluated and compared. The swarm techniques efficiency when applied to the DS-CDMA MuD (PSO-MuD and QPSO-MuD) in Flat Rayleigh channels is compared through the trade-off between performance and computational complexity. With the same simulation scenario, the comparison is accomplished among the PSO-MuD, QPSO-MuD, genetic algorithm (GA) and evolutionary programming with cloning (EP-C) algorithms. The complexity of these four heuristics-MuD (Heur-MuD) is compared, expressing it through the number of computational operations necessary in order to reach the performance obtained through the maximum likelihood detector (ML).