认知无线传感器网络频谱分配的一种改进方法

doi:10.19665/j.issn1001-2400.2020.03.011

摘要/Abstract

摘要：

为有效地分配和使用空闲频谱,提升认知无线传感器网络的频谱利用率,需要设计高效的频谱分配算法。针对认知无线传感器网络的频谱分配问题,提出了一种频谱分配的改进方法,设计了新的混沌动态克隆进化算法,建立了图论着色模型,推导了相应的适应度函数。设计了新的混沌算子、自适应算子和克隆算子以加快算法的收敛速度。通过仿真, 将混沌动态克隆进化算法与模拟退火算法、蚁群算法进行对比。仿真结果显示,相比蚁群算法与模拟退火算法,混沌动态克隆进化算法能够有效地提高全局搜索能力,频谱分配的网络效益值和系统的吞吐量有较明显的提高。

关键词: 无线传感器网络, 进化算法, 频谱分配, 认知无线电, 模拟退火算法

Abstract:

In order to effectively allocate the idle spectrum and improve spectrum utilization of cognitive wireless sensor networks, it is necessary to design an efficient spectrum allocation algorithm. Aiming at the problem of spectrum allocation in cognitive wireless sensor networks, an improved method for spectrum allocation is suggested. A new chaotic dynamic clonal evolution algorithm is designed. Then the graph theory coloring model is established with the corresponding fitness function derived. Traditional evolutionary algorithms have the problem of premature convergence, so chaotic operators, adaptive operators and cloning operators are added to the traditional evolutionary algorithms to accelerate the convergence of the algorithm. The chaotic dynamic clonal evolutionary algorithm is compared with the simulated annealing algorithm and the ant colony algorithm by simulation. The simulation results show that compared with the ant colony algorithm and the simulated annealing algorithm, the chaotic dynamic clonal evolution algorithm can effectively improve the global search ability, and significantly improve the network benefit value of spectrum allocation. The results also show that the proposed chaotic dynamic clonal evolution algorithm can make full use of existing spectrum resources and improve the system throughput.

Key words: wireless sensor networks, evolution algorithms, spectrum allocation, ant colony optimization, simulated annealing

中图分类号:

TN92

周杰,徐梦颖,王娇娇,卢毅. 认知无线传感器网络频谱分配的一种改进方法[J]. 西安电子科技大学学报, 2020, 47(3): 80-85.

ZHOU Ji,XU Mengying,WANG Jiaojiao,LU Yi. Improved scheme for spectrum allocation in cognitive wireless sensor networks[J]. Journal of Xidian University, 2020, 47(3): 80-85.

图/表 5

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系统参数	所算时间
系统参数	CACEA	ACO	SA
频带的数量设为5,用户数量为20	0.592	0.637	0.671
频带的数量设为5,用户数量为30	0.773	0.809	0.836