基于改进的量子遗传算法的认知无线网络频谱分配方法  

Spectrum allocation for cognitive radio networks based on improved quantum genetic algorithm

作　　者：刘刚[1] 赵海洋[1] 陈华[1] 郝晓辰[1] 

机构地区：[1]燕山大学河北省测试计量技术及仪器重点实验室,秦皇岛066004

出　　处：《高技术通讯》2015年第8期760-765,共6页Chinese High Technology Letters

基　　金：国家自然科学基金(61403336);河北省自然科学基金(F2015203291);秦皇岛市科学技术研究与发展计划(201401A037)资助项目

摘　　要：为了提高认知无线网络频谱分配的效果,根据认知无线网络的特性,提出了基于改进的量子遗传算法(IQGA)的认知无线网络频谱分配方法。该方法利用混沌搜索初始化种群染色体编码,在迭代过程中采用动态调整量子旋转角度更新染色体,并通过变异阈值对染色体进行选择性变异,最终将频谱分配的分配矩阵和基于混沌搜索的量子遗传算法的可行解相对应,以提高网络系统的平均效益为目标函数,实现空闲信道的合理分配。仿真结果表明,基于IQGA的认知无线网络频谱分配方法具有更快的收敛速度和更好的寻优性能,能有效地提高网络系统的整体效益。To improve the effect of spectrum allocation for cognitive radio networks, a new spectrum allocation method based on an improved quantum genetic algorithm （IQGA） is proposed according to the specific properties of cogni- tive radio networks. The method uses the chaotic searching to initialize the chromosome coding of population, up- dates the chromosome by dynamic adjustment of the quantum rotating angle during the iterative process, and uses the variation threshold for selective chromosome variation. Finally, it makes the allocation matrix for spectrum allo- cation correspond to the feasible solutions of the chaotic search based quantum genetic algorithm to achieve the rea- sonable allocation of the idle spectra with networks＇ average benefit as the objective function. The simulation re- suits show that the proposed IQGA based spectrum allocation method has the faster convergence speed and better optimization performance, and can increase networks＇ benefit effectively.

关 键 词：认知无线网络 频谱分配 量子遗传算法(QGA) 混沌搜索 变异阈值 

分 类 号：TN925[电子电信—通信与信息系统] TP18[电子电信—信息与通信工程]