On the use of artificial intelligence for MAI cancellation in DS/CDMA over Rayleigh fading channel with power control error

This study presents an easy approach based on neural networks (NN) to facilitate the computing of the bit error rate (BER) performance of a direct sequence code division multiple access (DS/CDMA) system over a Rayleigh multipath fading with power control error for both coherent and noncoherent reception, by producing the despreading sequences weighted (WDS) by stepping chip weighting waveforms. From the simulation results for this above method, we note that the BER performance does not undergo any degradation by using the parameters producing by the proposed method. This study presents an easy approach based on neural networks (NN) to facilitate the computing of the bit error rate (BER) performance of a direct sequence code division multiple access (DS/CDMA) system over a Rayleigh multipath fading with power control error for both coherent and noncoherent reception, by producing the despreading sequences weighted (WDS) by stepping chip weighting waveforms. From the simulation results for this above method, we note that the BER performance does not undergo any degradation by using the parameters producing by the proposed method.