Multi-user detection of DS-CDMA based on noise-ICA

Independent component analysis (ICA) is a signal processing technique that aims to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients. Making use of the independence of the user´s information in code division multiple access (CDMA) communication system, ICA based technique reduces multiple access interference (MAI). For traditional ICA algorithms ignore noise, in this paper Noise-ICA algorithm is proposed for multi-user detection of direct sequence code division multiple access (DS-CDMA) signal and compared with Infomax-ICA algorithm and Fast-ICA algorithm. The proposed algorithm takes advantage of negentropy estimation. 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 algorithm is more effective compared with traditional algorithms and performs better at separating the source signals from the mixed CDMA signals with noise.