New Blind Multiuser Detection in DS-CDMA Using H-DE and ICA Algorithms

Hyper Differential Evolution (H-DE)is a new optimization technique. We develop a novel blind Detection algorithm based on H-DE in conjunction with Independent Component Analysis (ICA). We then apply the algorithm to the multi-user symbol estimation problem in Direct Sequence Code Division Multiple Access (DS-CDMA) systems. Blind detection is to estimate multiple symbol sequences associated with all users in the downlink of the DS-CDMA communication system using only the received wireless data and without any knowledge of the user spreading codes. Bit error rate (BER) simulation evidence of the improved performance of this novel algorithm are shown for different number of users, signal to noise ratio (SNR) and different number of symbols per user. The performance is compared with the traditional FAST ICA Detector. The results show that the proposed algorithm performs well and outperforms the FAST ICA Detector in estimating the symbol signals from the mixed CDMA received signals.