基于信道排序的认知频谱分配算法  

A Cognitive Spectrum Allocation Algorithm Based on Channel Ranking

作　　者：蒋孜浩 郑安琪 秦宁宁 JIANG Zihao;ZHENG Anqi;QIN Ningning(Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education,Jiangnan University,Wuxi Jiangsu 214122,China)

机构地区：[1]江南大学轻工过程先进控制教育部重点实验室,江苏无锡214122

出　　处：《传感技术学报》2023年第10期1635-1642,共8页Chinese Journal of Sensors and Actuators

基　　金：国家自然科学基金项目(61702228);江苏省自然基金项目(BK20170198)。

摘　　要：针对认知传感网中均衡能耗的频谱分配问题,提出了一种适应信道的改进遗传算法(Adapt channel improved genetic algorithm,ACGA)进行频谱分配。为改良遗传算法中传统交叉方法运用于频谱分配问题时面临的交叉失效等问题,采用一种基于信道排序的交叉方案,以信道排序的增益作为交叉的限制,并利用个体相似度进行交叉基因的选取。为增加遗传变异的可靠性,采用了一种混合变异方案,利用博弈对个体进行良性变异,同时组合传统变异以控制种群的整体进化方向。仿真实验表明,相比传统的遗传算法,所提算法有着良好的寻优能力,可以有效降低网络的周期能耗。Aiming at the spectrum allocation problem of balanced energy consumption in cognitive sensor networks,an adapt channel improved genetic algorithm is proposed for spectrum allocation.In order to avoid the crossover failure and other problems faced by the traditional crossover method in the genetic algorithm when it is applied to the spectrum allocation problem,a crossover scheme based on channel sorting is adopted,and the selection of crossover gene is carried out according to individual similarity.To increase the reliability of genetic variation,a mixed mutation scheme is adopted,using games to mutate individuals benignly,while combining traditional mutations to control the overall evolutionary direction of the population.Simulation experiments show that,compared with the traditional genetic algorithm,the proposed algorithm has good optimization ability and can effectively reduce the periodic energy consumption of the network.

关 键 词：认知传感网 频谱分配 网络能耗 遗传算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]