摘要
为了实现认知无线网络频谱最优化分配,提出一种改进的和声搜索算法的认知无线网络频谱分配算法。首先,针对和声搜索算法易陷入局部最优,提出一种随机位置更新、反向学习策略、小概率变异和修正音调微调概率的改进和声搜索算法。其次,选择网络效益和比例公平性最大化为适应度函数,通过IHS优化选择获得频谱最优的无干扰分配矩阵,从而实现认知无线网络频谱最优化分配。与HS、GA和PSO相比,IHS频谱分配的网络效益和比例公平性最大,并且具有更快的收敛速度,分配策略更优。
In order to realize the optimal spectrum distribution in cognitive wireless network, an improved harmonic search algorithm for spectrum distribution in cognitive wireless network is proposed. Firstly, we put forward an improved harmony search algorithm with the properties of random position update, opposite learning strategy, small probability variation and modified tuning probability. Secondly, the optimal spectrum distribution of cognitive wireless networks is achieved by selecting the optimal spectrum distribution matrix to realize optimal spectrum without interference through IHS optimization. Compared with HS, GA, and PSO, the spectrum distribution based on IHS has the greatest network benefits and proportional fairness, faster convergence speed and better allocation strategy.
作者
郭腾
陈剑培
况富强
GUO Teng;CHEN Jianpei;KUANG Fuqiang(Heilongjiang Provincial Armed Police Corps,Harbin 150000,China;School of Electrical and Information Engineering,Yunnan University for Nationalities,Kunming 650500,China;Information Centre,Jiyuan Vocational and Technical College,Jiyuan 459000,China)
出处
《微型电脑应用》
2021年第3期97-99,105,共4页
Microcomputer Applications
关键词
频谱分配
反向学习
拓扑模型
和声搜索算法
网络效益
spectrum distribution
opposite learning
topology model
harmony search algorithm
network benefit