Reduced RBF centers based multi-user detection in DS-CDMA systems
ICHIT'06 Proceedings of the 1st international conference on Advances in hybrid information technology
Block PIC technique for synchronous CI/MC-CDMA system using neural network
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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We consider a multilayer perceptron neural network (NN) receiver architecture for the recovery of the information bits of a direct-sequence code-division-multiple-access (DS-CDMA) user. We develop a fast converging adaptive training algorithm that minimizes the bit-error rate (BER) at the output of the receiver. The adaptive algorithm has three key features: i) it incorporates the BER, i.e., the ultimate performance evaluation measure, directly into the learning process, ii) it utilizes constraints that are derived from the properties of the optimum single-user decision boundary for additive white Gaussian noise (AWGN) multiple-access channels, and iii) it embeds importance sampling (IS) principles directly into the receiver optimization process. Simulation studies illustrate the BER performance of the proposed scheme.