A Novel Technique for Multiple Access Interference Reduction in DS-CDMA Wireless Communications

In this paper, we present a comprehensive report on the research work focused on developing a novel concept for reducing Multiple Access Interference (MAI) in Direct Sequence – Code Division Multiple Access (DS-CDMA) systems prevailing in wireless communications. The proposed novel algorithm is developed by using the principles of artificial intelligence based on neural networks. The basic function of the algorithm is to determine interference ratio far more accurately even in the presence of very high noise in the channel. Subsequently, the simulation tests are carried out to validate the claim by using MATLAB and C++ platforms while considering higher data transfer rate, presence of AWGN and channel fading effects due to multi path reflections and diffractions. Finally performance analysis is done for bit error rate in comparison with floating point matched filter, parallel residue compensation, normalized least mean square, group-wise successive interference cancellation and partial parallel interference cancellation methods. The proposed intelligent algorithm has shown better results for bit error rate analysis. General Terms Wireless Communications, Neural Networks, MAI Algorithm