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

In this paper Improved-ICA (independent component analysis) algorithm is proposed for detection of DS-CDMA (direct sequence code division multiple access) signals and compared with JADE (Joint Approximation Diagonalization of Eigen matrices) and Fast-ICA algorithms. ICA based technique is based on independence of source signals and these conditions are satisfied in multi-user CDMA environment. The aim is to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients. Combining an ICA element to conventional signal detection reduces MAI (multiple access interference) and enables a robust, computationally efficient structure. For traditional ICA algorithm ignore noise, in this paper Improved-ICA algorithm considering the noise is proposed for multi-user DS-CDMA signal and compared with JADE and Fast-ICA algorithms. In this paper bit error rate simulations of these algorithms has been given for different number of users, SNR and compared. The results show that the proposed Improved-ICA is more effective compared with traditional algorithms and performs better at separating the source signals from the mixed CDMA signals with noise.