Computational intelligence techniques for multiuser detection of DS/CDMA signals
Computational intelligence techniques for multiuser detection of DS/CDMA signals
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DOI：
10.1109/cira.2003.1222121
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发表时间：
2003-07
期刊：
影响因子：
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通讯作者：
M. Shayesteh;M. Menhaj;H. Amindavar
中科院分区：
文献类型：
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作者：
M. Shayesteh;M. Menhaj;H. Amindavar
多址干扰和远近效应导致DS/CDMA系统中传统单用户检测器的性能下降。由于最优多用户检测器的复杂性较高，复杂度较低且性能合理的次优多用户检测器受到了相当多的关注。在本文中，我们应用计算智能技术，包括提出的改进遗传算法和多层感知器神经网络分析，用于 DS/CDMA 信号的多用户检测。我们从不同的角度比较它们的性能，例如计算复杂性、实现和错误率。我们还将它们的性能与 CDMA 中使用的其他检测器进行了比较。
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.