Multi-User Detection of DS-CDMA Based on Improved-FastICA

Abstract

Multi-user detection (MUD) is used to control multiple access interference (MAI) and promote system performance and capacity, which is one of the key technology for CDMA system. Independent component analysis (ICA) aims to recover a set of unknown mutually independent source signals from theirs observed mixtures without knowledge of the mixing coefficients. FastICA, one of the ICA methods, has been successfully applied in various fields. But the classical FastICA does not converge quickly. In multi-user detection of direct sequence code division multiple access (DS-CDMA) system, we proposes an Improved-FastICA algorithm to reduce multiple access interference (MAI). The improved-FastICA algorithm uses a new Fifth-order Newton iterative method to estimate the negentropy. The experimental results show that the improved algorithm has the advantages of smaller bit error rate than traditional algorithm. The Improved-FastICA is more suitable for applications in DS-CDMA system.