Computational intelligence techniques for multiuser detection of DS/CDMA signals

Multiple access interference and near-far effect cause the performance of the conventional single user detector in DS/CDMA systems to degrade. Due to high complexity of the optimum multiuser detector, suboptimal multiuser detectors with less complexity and reasonable performance have received considerable attention. In this paper we apply computational intelligence techniques including proposed modified genetic algorithm and our analysis of multilayer perceptron neural network for multiuser detection of DS/CDMA signals. We compare their performance form different points of view such as computational complexity, implementation and error rate. We also compare their performance with the other detectors used in CDMA.