New Blind Multiuser Detection in DS-CDMA Based on Extension of Efficient Fast Independent Component Analysis (EF-ICA)

This Paper develops a novel blind Detection algorithm based on Extension of Efficient FAST Independent Component Analysis (EF-ICA). classifying the received data to many parts in order to use a fit non-quadratic function to separate a non-Gaussian source. 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 several Blind Detectors based on Efficient FastICA and Fast ICA algorithms. The results show that the proposed algorithm performs well and outperforms the other Detectors in estimating the symbol signals from the mixed CDMA received signals.