电信科学 ›› 2016, Vol. 32 ›› Issue (5): 62-68.doi: 10.11959/j.issn.1000-0801.2016125

• 研究与开发 • 上一篇    下一篇

基于量子布谷鸟搜索的认知无线网络频谱分配

王先平1,曹卉2   

  1. 1 重庆文理学院软件工程学院，重庆 402160
    2 河南广播电视大学现代教育技术中心，河南 郑州 450000
  • 出版日期:2017-02-22 发布日期:2017-02-22
  • 基金资助:
    河南省科技厅基金资助项目“基于云存储的河南省终身教育海量数字化资源公共服务基础平台建模研究”;河南省科技厅基金资助项目“基于云存储的河南省终身教育海量数字化资源公共服务基础平台建模研究”;河南省教育厅基金资助项目“面向河南省社区远程教育的海量数字化教学资源存储管理研究”;河南省教育厅基金资助项目“面向河南省社区远程教育的海量数字化教学资源存储管理研究”

Spectrum allocation based on quantum cuckoo search algorithm in cognitive radio network

Xianping WANG1,Hui CAO2   

  1. 1 School of Software Engineering,Chongqing University of Arts and Sciences,Chongqing 402160,China
    2 Modern Education Technology Center,Henan Radio ＆ Television University,Zhengzhou 450000,China
  • Online:2017-02-22 Published:2017-02-22
  • Supported by:
    Henan Provincial Department of Science and Technology Project“the Public Service Platform of Massive Digital Resources of Henan Lifelong Education Based on Cloud Storage”;Henan Provincial Department of Science and Technology Project“the Public Service Platform of Massive Digital Resources of Henan Lifelong Education Based on Cloud Storage”;Henan Provincial Department of Education Project“Research on Storage Management of Massive Digital Teaching Resources for Community Distance Education in Henan”;Henan Provincial Department of Education Project“Research on Storage Management of Massive Digital Teaching Resources for Community Distance Education in Henan”

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摘要：

为了有效解决认知无线网络频谱分配的离散优化问题，将量子计算引入布谷鸟搜索算法，提出了一种新的组合优化算法——量子布谷鸟搜索算法。该算法使用量子鸟窝表征问题的多维解，通过Lévy flights随机游动方式和量子突变策略快速搜索到全局最优位置。通过使用基准函数验证了算法的高效性，并提出了一种基于量子布谷鸟搜索的认知无线网络频谱分配方法。然后与经典频谱分配算法在不同的网络效益函数下进行仿真性能比较。结果表明，所提出的频谱分配方法能够较快找到全局最优解，并且在不同网络效益函数下均优于已有的经典频谱分配算法。

关键词: 认知无线网络, 频谱分配, 离散优化问题, 量子计算, 布谷鸟搜索算法

Abstract:

There are discrete optimization problems for spectrum allocation in cognitive wireless network.A novel combinatorial optimization algorithm called quantum cuckoo search algorithm （QCSA）was proposed,which was based on quantum computing and cuckoo search algorithm.The quantum nest was used to represent multiple dimensionality solution for the optimization problem,and the global optimal position was found according to Lévy flights and quantum mutation strategy.In additional,some classical benchmark functions were employed to prove the effectiveness of QCSA,and a spectrum allocation method based on QCSA was proposed for cognitive network.Compared with classical spectrum allocation methods by using different network utility functions,the global optimal solution can be searched so fast.Simulation results show that the proposed spectrum allocation method based on QCSA is better than other traditional methods under different network utility functions.

Key words: cognitive wireless network, spectrum allocation, discrete optimization problem, quantum computing, cuckoo search algorithm

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