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协作通信系统中继功率分配算法的研究
引用本文:范立娜,汪晋宽,高静,吕腊梅. 协作通信系统中继功率分配算法的研究[J]. 东北大学学报(自然科学版), 2017, 38(9): 1222-1225. DOI: 10.12068/j.issn.1005-3026.2017.09.002
作者姓名:范立娜  汪晋宽  高静  吕腊梅
作者单位:(1. 东北大学秦皇岛分校 控制工程学院, 河北 秦皇岛066004; 2. 东北大学 信息科学与工程学院, 辽宁 沈阳110819)
基金项目:国家自然科学基金资助项目(61403069); 河北省自然科学基金资助项目(F2014501055); 中央高校基本科研业务费专项资金资助项目(N162304003).
摘    要:研究了协作通信系统中功率分配的问题,主要研究了固定放大转发协议下单中继系统的功率分配.首先对系统的误码率进行了推导并以最小化系统的误码率为目标对优化问题进行了定义;其次引入惩罚因子将有约束的最小误码率优化问题转化为无约束优化问题进而建立新的目标函数;最后提出了人工鱼群和粒子群相结合的算法对系统优化问题进行了求解.仿真结果表明所提算法提升了系统的性能并降低了计算复杂度.

关 键 词:功率分配  协作通信  中继  人工鱼群  粒子群优化  

Research on Relay Power Allocation Algorithm for Cooperative Communication Systems
FAN Li-na,WANG Jin-kuan,GAO Jing,LYU La-mei. Research on Relay Power Allocation Algorithm for Cooperative Communication Systems[J]. Journal of Northeastern University(Natural Science), 2017, 38(9): 1222-1225. DOI: 10.12068/j.issn.1005-3026.2017.09.002
Authors:FAN Li-na  WANG Jin-kuan  GAO Jing  LYU La-mei
Affiliation:1. School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China; 2. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
Abstract:Power allocation of the cooperative communications was investigated, as well as an optimal power allocation of single relay system with amplify-and-forward (AF) protocol. The instantaneous symbol error rate (SER) for the AF relay system was derived first and the objective of optimization by minimizing the system error rate was defined. Secondly, the penalty factor was introduced to transform the constrained minimum bit error rate problem into an unconstrained problem and then a new objective function was established. Finally, a combination of artificial fish swarm and particle swarm optimization algorithm(AFPSO) was proposed to solve the system optimization problem. Simulation result shows that the proposed algorithm can improve the system performance and reduce the computational complexity.
Keywords:power allocation  cooperative communications  relay  artificial fish swarm  particle swarm optimization  
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