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基于混合鲸鱼优化算法的鲁棒多用户检测 预览

Robust Multiuser Detection Based on Hybrid Whale Optimization Algorithm
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摘要 针对冲击噪声环境下多用户检测误码率高的问题,提出一种基于混合鲸鱼优化的鲁棒多用户检测算法。该算法首先利用基于非线性控制策略的改进鲸鱼优化算法,加速寻优算法迭代过程的收敛;再利用自适应差分进化算法丰富算法种群个体信息,增强优化算法的全局收敛性;同时将适应度较好的个体信息保存到集合中,以保证下一次迭代寻优方向的可靠性,最终实现对最优解位置的快速解算。仿真结果表明,基于本文算法设计的多用户检测器相比采用遗传算法、差分进化算法,以及鲸鱼优化算法的多用户检测器寻优迭代次数更少,且误码率低。 A robust multiuser detection algorithm based on hybrid whale optimization is proposed to solve the problem of high bit error rate of multiuser detection under impulse noise environment.Firstly,the improved whale optimization algorithm based on the non-linear control strategy is used to accelerate the convergence of the iteration process of the optimization algorithm.Then,the adaptive differential evolution algorithm is used to enrich the individual information of the population and enhance the global convergence of the optimization algorithm.At the same time,the individual information with good fitness is saved in a set to ensure the reliability of the optimization direction of the next iteration,and finally,a fast resolution to the position of the optimal solution is achieved.The simulation results show that the multi-user detector based on the proposed algorithm has fewer iterations and lower bit error rate than the multi-user detector based on genetic algorithm,differential evolution algorithm and whale optimization algorithm.
作者 孙希延 范灼 纪元法 SUN Xi-yan;FAN Zhuo;JI Yuan-fa(School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China;Guangxi Key Laboratory of Precision Navigation Technology and Application,Guilin University of Electronic Technology,Guilin 541004,China;State and Local Joint Engineering Research Center for Satellite Navigation and Location Service,Guilin University of Electronic Technology,Guilin 541004,China;Guangxi InformationScience Experiment Center,Guilin University of Electronic Technology,Guilin 541004,China)
出处 《科学技术与工程》 北大核心 2019年第13期114-119,共6页 Science Technology and Engineering
基金 国家重点研发计划资助(2018YFB0505103) 国家自然科学基金(61561016,61861008) 广西科技厅项目(桂科AC16380014,桂科AA17202048,桂科AA17202033) 四川科技计划项目(17ZDYF1495) 桂林科技局项目(20160202,20170216) 广西高校中青年教师基础能力提升项目(ky2016YB164) 桂林电子科技大学研究生教育创新计划资助项目(2018YJCX19)资助.
关键词 鲸鱼优化算法 差分进化算法 混合鲸鱼优化 多用户检测 冲击噪声 whale optimization algorithm differential evolution algorithm hybrid whale optimization multiuser detection impulse noise
作者简介 第一作者:孙希延(1973-),女,汉族,山东潍坊人,博士,研究员。研究方向:卫星导航。E-mail:sunxiyan1@163.com。
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