混沌量子克隆算法求解认知无线网络频谱分配问题

柴争义; 刘芳; 朱思峰

doi:10.7498/aps.60.068803

摘要

对认知无线网络中的频谱进行有效分配是实现动态频谱接入的关键技术.考虑3次用户对频谱的需求和分配的公平性,给出了频谱分配的数学模型,并将其转换为以最大化网络收益为目标的带约束优化问题,进而提出一种采用混沌量子克隆优化求解的认知无线网络频谱分配算法, 并证明了该算法以概率1收敛.最后,通过仿真实验比较了本文算法与颜色敏感图着色算法、基于遗传算法的频谱分配、基于量子遗传算法的频谱分配的性能.结果表明:本文算法性能较优, 能更好地实现网络收益最大化.

关键词:

Abstract

Efficient spectrum allocation of cognitive wireless network is the key technology to dynamic spectrum access. Taking into account the needs of secondary users for the spectrum and the fairness allocation of the spectrum, mathematical model of spectrum allocation is given, and then it is converted into a constrained optimization problem with the goal of maximizing network profits. A chaos quantum clonal optimization algorithm is proposed to solve the problem, and then the convergence of the algorithm with probability 1 is proved. Finally, the simulation experiments are done to test the algorithm. The results show that compared with the color-sensitive graph coloring algorithm, the spectrum allocation based on genetic algorithm, and the spectrum allocation based on quantum-inspired genetic algorithm, the algorithm has good performances. It can achieve the maximization of network profits.

Keywords:

作者及机构信息

(1)西安电子科技大学计算机学院, 西安 710071; (2)西安电子科技大学计算机学院, 西安 710071;河南工业大学信息科学与工程学院, 郑州 450001

基金项目: 国家高技术研究发展计划(批准号:2009AA12Z210)、国家自然科学基金 (批准号:61001202,61072139和61003199)、高等学校博士学科点专项科研基金(批准号:20090203120016,20100203120008)和郑州市科技发展计划(批准号:2010GYXM374)资助的课题.

Authors and contacts

(1)School of Computer Science and Technology, Xidian University, Xi'an 710071, China; (2)School of Computer Science and Technology, Xidian University, Xi'an 710071, China; School of Information Science and Engineering, Hennan University of Technology, Zhengzhou 450001, China

参考文献

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施引文献

[1]	Akyildlz I, Li W Y, Vuran M 2006 Comput. Netw. J. 9 2127
[2]	Ji Z, Liu K J R 2007 IEEE Comm. Mag. 45 88
[3]	Niyato D, Hossain E 2008 IEEE J. Sel. Area Comm. 26 192
[4]	Zou C, Jin T, Chigan C 2008 Comput. Netw. 52 864
[5]	Huang L Y, Liu C, Wang S P 2010 J. Commun. 31 136 (in Chinese) [黄丽亚、刘臣、王锁萍 2010 通信学报 31 136]
[6]	Gandhi S, Buragohain C, Cao L L 2007 IEEE Commun. Mag. 32 22
[7]	Ji Z, Liu K J R 2008 IEEE J. Sel. Area Commun. 26 182
[8]	Wang F, Krunz M, Cui S 2008 IEEE J. Sel. Top. Signa. 2 74
[9]	Gandhi S, Buragohain C, Cao L 2008 Comput. Netw. 52 879
[10]	Xu Y Y, Gao L 2009 J. Univ. Sci. Technol. Chin. 39 1064 (in Chinese) [徐友云、高林 2009 中国科学技术大学学报39 1064]
[11]	Wang W, Liu X 2005 IEEE Vehicular Technology Conference Dallas, USA September 25—28, 2005 p690
[12]	Peng C Y, Zheng H T, Zhao B Y 2006 Mobile Netw. Appl. 11 555
[13]	Liao C L, Chen J, Tang Y X, Liao S Q 2007 J.Electr. Inf. Technol. 29 1608 (in Chinese)[廖楚林、陈劫、唐友喜、廖少谦 2007 电子与信息学报 29 1608]
[14]	Hao D D, Zhou S H, Cheng S D 2008 J. Software 19 479 (in Chinese)[郝丹丹、邹仕洪、程时端 2008 软件学报 19 479]
[15]	Zhao Z Z, Peng Z, Zheng S L, Shang J N 2009 IEEE Trans. Wirel. Commun. 8 4421
[16]	Zhao Z Z, Peng Z, Zheng S L, Xu S Y, Lou C Y, Yang X N 2009 Acta. Phys. Sin. 58 1358 (in Chinese)[赵知劲、彭振、郑仕链、徐世宇、楼才义、杨小牛 2009 物理学报 58 1358]
[17]	Zheng S L, Lou C Y, Yang X N 2010 Acta. Phys. Sin. 59 3611 (in Chinese)[郑仕链、楼才义、杨小牛 2010 物理学报 59 3611]
[18]	Li Y Y, Jiao L C 2007 Chin. J. Comp. 30 176 (in Chinese)[李阳阳、焦李成 2007 计算机学报 30 176]
[19]	Wu Q Y, Jiao L C, Li Y Y 2009 Prog. Nat. Sci. 19 1341
[20]	Du, H F, Gong M G, Liu R C 2009 Sci. China Ser. F 19 237

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