Minimum probability of error for asynchronous Gaussian multiple-access channels
IEEE Transactions on Information Theory
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Stochastic methods for dynamic OVSF code assignment in 3G networks
SAGA'07 Proceedings of the 4th international conference on Stochastic Algorithms: foundations and applications
Stochastic optimization algorithm based dynamic resource assignment for 3G systems
NEW2AN'07 Proceedings of the 7th international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking
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The conventional single user detector in DS/CDMA (Direct Sequence Code Division Multiple Access) systems involves multiple access interference and the near-far effect which cause the limitation of capacity. On the other hand, the computational complexity of the optimum multiuser detector grows exponentially with the number of users. There has been a lot of interest in suboptimal multiuser detectors with less complexity and reasonable performance. In this paper we apply the classic and a new modified genetic algorithm for multiuser detection of DS/CDMA signals. It is shown that the classic genetic algorithm (GA) reaches an error floor at high signal to noise ratios while the proposed method has higher performance than the classic one and comparable to the optimum single user detector with much less complexity than the optimum multiuser detector.