基于量子布谷鸟搜索的认知无线网络频谱分配

王先平; 曹卉

doi:10.11959/j.issn.1000-0801.2016125

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基于量子布谷鸟搜索的认知无线网络频谱分配

研究与开发 | 更新时间：2024-06-05

- 基于量子布谷鸟搜索的认知无线网络频谱分配
- Spectrum allocation based on quantum cuckoo search algorithm in cognitive radio network
- 电信科学 2016年32卷第5期页码：62-68
- 作者机构：
  
  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
- 作者简介：
  
  [ "王先平（1972-），男，重庆文理学院软件工程学院讲师，主要研究方向为算法理论和应用。" ]
  [ "曹卉（1982-），女，河南广播电视大学现代教育技术中心讲师，主要研究方向云计算、大数据数据分析。" ]
- 基金信息：
  
  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”;Henan Provincial Department of Science and Technology Project“the Public Service Platform of Massive Digital Resources of Henan Lifelong Education Based on Cloud Storage”(152102210304);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”;Henan Provincial Department of Education Project“Research on Storage Management of Massive Digital Teaching Resources for Community Distance Education in Henan”(ZJA15172)
- DOI：10.11959/j.issn.1000-0801.2016125
  中图分类号： TP311
- 网络出版日期：2016-05，
  
  纸质出版日期：2016-05-20
- 稿件说明：
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王先平, 曹卉. 基于量子布谷鸟搜索的认知无线网络频谱分配[J]. 电信科学, 2016,32(5):62-68.

Xianping WANG, Hui CAO. Spectrum allocation based on quantum cuckoo search algorithm in cognitive radio network[J]. Observation and communication, 2016, 32(5): 62-68.
王先平, 曹卉. 基于量子布谷鸟搜索的认知无线网络频谱分配[J]. 电信科学, 2016,32(5):62-68. DOI： 10.11959/j.issn.1000-0801.2016125.

Xianping WANG, Hui CAO. Spectrum allocation based on quantum cuckoo search algorithm in cognitive radio network[J]. Observation and communication, 2016, 32(5): 62-68. DOI： 10.11959/j.issn.1000-0801.2016125.

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。

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.

关键词

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references

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