| 基于克隆选择算法和神经网络的多用户检测 |
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| 引用本文： | 高洪元,庞伟正.基于克隆选择算法和神经网络的多用户检测[J].哈尔滨商业大学学报(自然科学版),2004,20(5):543-546. |
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| 作者姓名： | 高洪元 庞伟正 |
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| 作者单位： | 哈尔滨工程大学,信息与通信工程学院,黑龙江,哈尔滨,150001 |
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| 摘 要： | 针对传统检测器和最佳检测器在多用户检测中存在的缺点,利用克隆选择算法和Hopfield神经网络在解决优化问题的优势,提出了一种基于改进的克隆选择算法和神经网络的准最佳多用户检测器并用计算机进行仿真.仿真结果证明了该多用户检测器有良好的抗多址干扰和抗"远近效应"的能力,并有计算复杂度低和易于实时实现的优点.
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| 关 键 词： | CDMA 多用户检测 克隆选择算法 Hopfield神经网络 |
| 文章编号： | 1672-0946(2004)05-0543-03 |
| 修稿时间： | 2004年6月11日 |
Study on multi-user detection based on clonal selection algorithm and neural network |
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| GAO Hong-yuan,PANG Wei-zheng.Study on multi-user detection based on clonal selection algorithm and neural network[J].Journal of Harbin University of Commerce :Natural Sciences Edition,2004,20(5):543-546. |
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| Authors: | GAO Hong-yuan PANG Wei-zheng |
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| Abstract: | In order to solve the disadvantages of the conventional detector and the optimum detector in multi-user detection, this paper utilized optimum performance of clonal selection algorithm and Hopfield neural network to deal with the optimum problem and design a new detector based on clonal selection algorithm and Hopfield neural network(CSAHNND). Simulation results showed that CSAHNND not only has a good ability in aspects of multiple-access interference and near-far resistance, but also is of less numerical computation and more efficient. |
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| Keywords: | CDMA multi-user detection clonal selection algorithm Hopfield neural network |
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