摘要
针对无线频谱资源利用率低的问题,提出一种基于改进云量子遗传算法(MCQGA)的动态频谱分配方法。该方法可动态调整量子门旋转角,基于云理论进行交叉和变异操作,以图论着色模型为基础,综合考虑最大化平均系统收益、最大化最小带宽和最大化比例公平性度量进行频谱分配。选取粒子群算法、传统遗传算法和基本量子遗传算法进行对比仿真实验,仿真结果表明,该方法更适用于解决频谱分配问题。
A Dynamic Spectrum Allocation(DSA)method is proposed to solve the problem of low utilization of wireless spectrum resources based on Modified Cloud Quantum Genetic Algorithm(MCQGA).The method can adjust the rotation angle of the quantum gate dynamically,and uses the cloud theory to cross and mutate.According to the graph theory coloring model,the maximum sum of mean reward,the maximum minimum bandwidth and the maximum proportional fairness measures are considered for spectrum allocation.Particle swarm optimization algorithm,traditional genetic algorithm and basic quantum genetic algorithm are selected for comparative simulation experiment.Simulation results show that the proposed method is more suitable for spectrum allocation.
作者
焦传海
杜奕航
JIAO Chuanhai;DU Yihang(Army Academy of Artillery and Air Defense,Hefei Anhui 230031,China;63rd Institute,National University of Defense Technology,Nanjing Jiangsu 210007,China)
出处
《太赫兹科学与电子信息学报》
2021年第3期465-470,共6页
Journal of Terahertz Science and Electronic Information Technology
关键词
认知无线电
动态频谱分配
群智能算法
改进云量子遗传算法
Cognitive Radio(CR)
Dynamic Spectrum Allocation
swarm intelligence algorithm
Modified Cloud Quantum Genetic Algorithm
作者简介
焦传海(1983-),男,博士,讲师,主要研究方向为认知无线电、电磁频谱感知与分配等。email:jiao_chuanhai@126.com。
