Comparison and Performance Analysis of DS-CDMA Systems by Genetic, Neural and GaNN (hybrid) Models

Direct Sequence-Code Division Multiple Access (DS-CDMA) technique is used in cellular systems where users in the cell are separated from each other with their unique spreading codes. DS-CDMA has been used extensively which suffers from multiple access interference (MAI) and inter symbol interference (ISI) due to multipath nature of channels in presence of additive white Gaussian noise (AWGN). Spreading codes play an important role in multiple access capacity of DS-CDMA system and Walsh sequences are used as spreading codes in DS-CDMA. DS CDMA receiver namely genetic algorithm neural network and GaNN (hybrid) based MUD receiver for DS-CDMA communication using Walsh sequences is designed. The performance of the same will be compared among themselves

Multiuser Detection with Neural Network MAI Detector in CDMA Systems for AWGN and Rayleigh Fading Asynchronous Channels

In this study, the performance of the proposed receiver with the neural network Multiple Access Interference (MAI) detector is compared with the matched filter bank (classical receiver), neural network that detects user's signal and single user bound for Additive White Gaussian Noise (AWGN) and Rayleigh fading asynchronous channels by computer simulations. There are a lot of study in the literature that compare the neural network receiver and other methods. These neural network receivers detect the user bits after the matched filter. In this study, MAI is detected after the matched filter with the proposed neural network receiver and then user bits are obtained by subtracting MAI from the matched filter output. The proposed receiver with the neural network MAI detector has got better Bit Error Rate (BER) performance than the neural network that detects user's signal in AWGN and Rayleigh fading asynchronous channels for Signal Noise Ratio (SNR) simulations, and in AWGN asynchronous channels for the number of users simulations, although both have the same complexity. However, both have almost same BER performance in AWGN and Rayleigh fading asynchronous channels for Near Far Ratio (NFR) simulations, and in Rayleigh fading asynchronous channels for the number of users simulations