混沌免疫多目标算法求解认知引擎参数优化问题

柴争义; 陈亮; 朱思峰

doi:10.7498/aps.61.058801

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摘要

合理的认知引擎参数设置可以提高频谱的使用性能. 通过分析认知无线网络中的认知引擎参数配置, 给出了其数学模型, 并将其转化为一个多目标优化问题, 进而提出一种基于混沌免疫多目标优化的求解方法. 算法使用Logistic混沌映射初始化种群, 并在每一代将混沌特性用于最优解集的搜索; 设计了适合此问题的免疫克隆算子和抗体群更新算子, 保证了Pateto最优解集分布的多样性和均匀性. 最后, 在多载波环境下对算法进行了仿真实验. 结果表明, 算法可以根据信道条件和用户服务的动态变化, 自适应调整各个子载波的发射功率和调制方式, 可以求出更多满足偏好需求的解, 满足认知引擎参数优化要求.

关键词:

作者及机构信息

1.
河南工业大学信息科学与工程学院, 郑州 450001;

2.
西安电子科技大学计算机学院, 西安 710071

基金项目: 国家高技术研究发展计划(863计划)(批准号: 2009AA12Z210)、国家自然科学基金(批准号: 61001202, 61003199和61072139)、教育部博士点基金(批准号: 20090203120016和20100203120008)、中央高校基本科研业务费专项资金(批准号: JY10000902001)和博士后面上基金(批准号: 20090461283) 资助的课题.

参考文献

[1]	Haykin S 2008 IEEE J. Sel. Area Comm. 23 201
[2]	Tim R N, Brett A B, Alexander M 2008 Wirel. Commun. Mob.Com. 7 1129
[3]	Zhao Z J, Zheng S L, Shang J N, Kong X Z 2007 Acta Phys. Sin.56 6760 (in Chinese) [赵知劲, 郑仕链, 尚俊娜, 孔宪正 2007 物理学报 56 6760]
[4]	Ayman E H 2009 The Ninth IEEE Malaysia International Conferenceon Communications, Chicago, July 21-23, 2009 p1
[5]	Zhao Z J, Xu S Y, Zheng S L, Yang X N 2009 Acta Phys. Sin. 585118 (in Chinese) [赵知劲, 徐世宇, 郑仕链, 杨小牛 2009 物理学报 58 5118]
[6]	Zhao N, Li S Y, Wu Z L 2011 Wire. Per. Comm. 58 1
[7]	Yang D D, Jiao L C, Gong M G, Feng J 2010 Comput. Intell. 26359
[8]	Chai Z Y, Liu F 2011 J. Commun. 31 591 (in Chinese) [柴争义, 刘芳 2011 通信学报 31 591]
[9]	Chai Z Y, Liu F, Zhu S F 2011 Acta Phys. Sin. 60 068803 (inChinese) [柴争义, 刘芳, 朱思峰 2011 物理学报 60 068803]
[10]	Zu Y X, Zhou J, Zeng C C 2010 Chin. Phys. B 19 119501
[11]	Zheng R R, Liu Y A 2010 Acta Elec. Sin. 38 632 (in Chinese) [张然然, 刘元安 2010 电子学报 38 632]
[12]	Ycek T, Arslan H 2009 IEEE Comm. 1 116
[13]	Zhou J, Zu Y X 2010 Acta Phys. Sin. 59 7508 (in Chinese) [周杰, 俎云霄 2010 物理学报 59 7508]
[14]	Gong M G, Jiao L C, Liu F, Ma W P 2010 Knowl. Inf. Syst. 25523
[15]	Lei D M, Yan X P, Wu Z M 2006 Acta Elec. Sin. 34 1142
[16]	Newman T R, Evans J B 2008 The 3rd IE-EE Symposium on NewFrontiers in Dynamic Spectrum Access Networks, Chicago, March10-12, 2008 p1
[17]	Rieser C J 2006 (Ph. D. Dissertation) (Virginia:Virginia Tech)
[18]	Mackenzie A B, Reed J H 2009 IEEE Comm. Lett. 97 660
[19]	Zhang C Y, Dong X, Wang X J 2010 J. Mech. Eng. 46 156 (inChinese) [张超勇, 董星, 王晓娟 2010 机械工程学报 46 156]
[20]	Zhou X S, Jiong S, Jian X 2010 J. S. E. Univ. 26 563

施引文献

[1]	Haykin S 2008 IEEE J. Sel. Area Comm. 23 201
[2]	Tim R N, Brett A B, Alexander M 2008 Wirel. Commun. Mob.Com. 7 1129
[3]	Zhao Z J, Zheng S L, Shang J N, Kong X Z 2007 Acta Phys. Sin.56 6760 (in Chinese) [赵知劲, 郑仕链, 尚俊娜, 孔宪正 2007 物理学报 56 6760]
[4]	Ayman E H 2009 The Ninth IEEE Malaysia International Conferenceon Communications, Chicago, July 21-23, 2009 p1
[5]	Zhao Z J, Xu S Y, Zheng S L, Yang X N 2009 Acta Phys. Sin. 585118 (in Chinese) [赵知劲, 徐世宇, 郑仕链, 杨小牛 2009 物理学报 58 5118]
[6]	Zhao N, Li S Y, Wu Z L 2011 Wire. Per. Comm. 58 1
[7]	Yang D D, Jiao L C, Gong M G, Feng J 2010 Comput. Intell. 26359
[8]	Chai Z Y, Liu F 2011 J. Commun. 31 591 (in Chinese) [柴争义, 刘芳 2011 通信学报 31 591]
[9]	Chai Z Y, Liu F, Zhu S F 2011 Acta Phys. Sin. 60 068803 (inChinese) [柴争义, 刘芳, 朱思峰 2011 物理学报 60 068803]
[10]	Zu Y X, Zhou J, Zeng C C 2010 Chin. Phys. B 19 119501
[11]	Zheng R R, Liu Y A 2010 Acta Elec. Sin. 38 632 (in Chinese) [张然然, 刘元安 2010 电子学报 38 632]
[12]	Ycek T, Arslan H 2009 IEEE Comm. 1 116
[13]	Zhou J, Zu Y X 2010 Acta Phys. Sin. 59 7508 (in Chinese) [周杰, 俎云霄 2010 物理学报 59 7508]
[14]	Gong M G, Jiao L C, Liu F, Ma W P 2010 Knowl. Inf. Syst. 25523
[15]	Lei D M, Yan X P, Wu Z M 2006 Acta Elec. Sin. 34 1142
[16]	Newman T R, Evans J B 2008 The 3rd IE-EE Symposium on NewFrontiers in Dynamic Spectrum Access Networks, Chicago, March10-12, 2008 p1
[17]	Rieser C J 2006 (Ph. D. Dissertation) (Virginia:Virginia Tech)
[18]	Mackenzie A B, Reed J H 2009 IEEE Comm. Lett. 97 660
[19]	Zhang C Y, Dong X, Wang X J 2010 J. Mech. Eng. 46 156 (inChinese) [张超勇, 董星, 王晓娟 2010 机械工程学报 46 156]
[20]	Zhou X S, Jiong S, Jian X 2010 J. S. E. Univ. 26 563

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混沌免疫多目标算法求解认知引擎参数优化问题

1. 河南工业大学信息科学与工程学院, 郑州 450001;

2. 西安电子科技大学计算机学院, 西安 710071

基金项目:

国家高技术研究发展计划(863计划)(批准号: 2009AA12Z210)、国家自然科学基金(批准号: 61001202, 61003199和61072139)、教育部博士点基金(批准号: 20090203120016和20100203120008)、中央高校基本科研业务费专项资金(批准号: JY10000902001)和博士后面上基金(批准号: 20090461283) 资助的课题.

收稿日期: 2011-03-15

修回日期: 2011-07-04

刊出日期: 2012-03-05

摘要: 合理的认知引擎参数设置可以提高频谱的使用性能. 通过分析认知无线网络中的认知引擎参数配置, 给出了其数学模型, 并将其转化为一个多目标优化问题, 进而提出一种基于混沌免疫多目标优化的求解方法. 算法使用Logistic混沌映射初始化种群, 并在每一代将混沌特性用于最优解集的搜索; 设计了适合此问题的免疫克隆算子和抗体群更新算子, 保证了Pateto最优解集分布的多样性和均匀性. 最后, 在多载波环境下对算法进行了仿真实验. 结果表明, 算法可以根据信道条件和用户服务的动态变化, 自适应调整各个子载波的发射功率和调制方式, 可以求出更多满足偏好需求的解, 满足认知引擎参数优化要求.

关键词:

Parameter optimization of cognitive engine based on chaos multi-objective immune algorithm

1.
School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China;

2.
School of Computer Science and Technology, Xidian University, Xi'an 710071, China

Fund Project:

Project supported the National High Technology Research and Development Program of China (Grant No. 2009AA12Z210), the National Natural Science Foundation of China (Grant Nos. 61001202, 61003199, 61072139), the National Research Foundation for the Doctoral Program of Higher Education of China (Grant Nos. 20090203120016 and 20100203120008), the Fundamental Research Funds for the Central Universities (Grant No. JY10000902001), and the Postdoctoral Science Foundation Funded Project of China (Grant No. 20090461283).

Received Date: 15 March 2011

Accepted Date: 04 July 2011

Published Online: 05 March 2012

Abstract: Reasonable setting of engine parameters can improve the performance of the spectrum use. By analyzing engine parameter adjustment of cognitive wireless network, the mathematical model is given, and then it is converted into a multi-objective optimization problem. A chaos multi-objective immune algorithm is proposed to solve the problem. Logistic mapping is used to initialize population and search for the best solutions in every generation. The operators of cloning and antibodies updating are designed, which ensures that the distribution of Pateto optimal solutions is more diverse and uniform. Finally, the simulation experiments are done to test the algorithm under multi-carrier system. The results show that the algorithm can adjust transmission power and modulation mode according to the change of channel and user demands. More solutions with preferences are obtained, so it meets the demands for parameter optimization of cognitive engine.

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