Multi-User Detection based on PSO-KICA

Abstract

Multi-user detection (MUD) is used to reduce multiple access interference (MAI) and promote system performance and capacity, which is one of the core technologies for CDMA system. In this paper, some questions of blind MUD based on independent component analysis (ICA) are introduced firstly, and then a k ernel independent component analysis (KICA) algorithm which brings in a new hybrid kernel function is proposed. In addition, the particle swarm optimization (PSO) algorithm is studied and it is devoted to the optimizing process of the KICA algorithm. The improved PSO-KICA algorithm can solve the issues that the objective function falls into the local optimum. The experimental results show that the PSO-KICA algorithm has the smaller bit error rate and good convergent speed than the classical ICA algorithm.