多用户场景下SWIPT-NOMA网络中的保密能量效率优化  

Research on secure energy efficiency optimization in SWIPT-NOMA network in multi-user scenes

作　　者：薛亮[1] 王缙 王金龙 王燕龙 Xue Liang;Wang Jin;Wang Jinlong;Wang Yanlong(School of Information&Electrical Engineering,Hebei University of Engineering,Handan Hebei 056038,China;College of Electrical Engineering&Automation,Fuzhou University,Fuzhou 350108,China;School of Information&Communication Engineering,Beijing University of Posts&Telecommunications,Beijing 100876,China)

机构地区：[1]河北工程大学信息与电气工程学院,河北邯郸056038 [2]福州大学电气工程与自动化学院,福州350108 [3]北京邮电大学信息与通信工程学院,北京100876

出　　处：《计算机应用研究》2021年第10期3115-3119,3124,共6页Application Research of Computers

基　　金：国家自然科学基金资助项目(61973085);河北省自然科学基金资助项目(F2016402054);河北省高等学校科学研究计划项目(BJ2014019,ZD2015087,QN2015046);河北省人才培养工程项目(A2016002023)。

摘　　要：在采用非正交多址接入技术的无线携能通信网络中,窃听者的存在和不同用户配对方式将影响网络的保密能量效率。为寻求保密能量效率最大化支配下的网络资源配置方案,提出了一种改进的群智能搜索算法用于解决此非凸优化问题。改进的群智能搜索算法采用共生生物搜索技术,增强了对可行域的局部搜索能力。仿真结果表明,不同的用户配对方式在单时隙或多时隙场景下具有相异特征,改进后的群智能搜索算法比其他基线算法具有更佳的网络性能,为多输入多输出非正交多址接入无线携能通信网络中通信安全及能量效率的研究提供了依据。The existence of eavesdropper and the matching of users affect the secure energy efficiency of the NOMA SWIPT network.In order to find a network resource allocation scheme dominated by maximum secure energy efficiency,this paper proposed an improved swarm intelligence search algorithm to solve the non-convex optimization problem.The improved swarm intelligence search algorithm used the symbiosis organism search to enhance the local search ability in the feasible region.Simulation results show that different user pairing methods have different characteristics in single slot or multiple slot scenarios,and the improved swarm intelligence search algorithm has better network performance than other baseline algorithms.It provides a basis for the research of communication security and energy efficiency in SWIPT network combined with MIMO and NOMA.

关 键 词：无线携能通信 非正交多址接入 保密能量效率 群智能搜索 

分 类 号：TP393.04[自动化与计算机技术—计算机应用技术]