基于改进的克隆选择算法的多用户检测技术

Applied Improved Clonal Selection Algorithm to Multiuser Detection

根据克隆选择原理的免疫机理,提出了一种改进的克隆选择算法(CSA),进而设计了2种码分多址(CDMA)多用户检测器:一种方法是混合Hopfield神经网络和克隆选择算法;另一种方法是把多阶段检测器MSD嵌入到克隆选择算法的每一代中。通过混合MSD到克隆选择算法中,可以加快克隆选择算法的收敛速度,减少计算复杂度。另外,克隆选择算法所提供的好的初值可以改善MSD的性能,嵌入的MSD还改善了克隆选择算法的性能。仿真结果证明了该方法无论抗多址干扰能力和抗远近效应能力都优于传统方法和一些应用优化算法的多用户检测器。

According to the immune mechanism of the clonal selection algorithm, an improved clonal selection algorithm （CSA） is proposed. Two kinds of the multiuser detectors in code-division multiple access （CDMA） communications system are designed. One of the methods is that the Hopfield neural network is embedded and hybridized into the CSA,and the other is that the multistage detector （MSD） is embedded into the CSA at each generation. Such a hybridization of the CSA with the MSD reduces its computational complexity by providing faster convergence. In addition,a better initial data estimate supplied by the CSA improves the performance of the MSD,and the embedded MSD improves the performance of the CSA. Simulation results show that the proposed approaches of multi-user detection have significant performance improvements over the detectors based on the previous algorithm in terms of bit-error-rate,multiple access interference and nea-far resistance.