电子学报 ›› 2015, Vol. 43 ›› Issue (8): 1526-1530.DOI: 10.3969/j.issn.0372-2112.2015.08.009

• 学术论文 • 上一篇    下一篇

拟态物理学多目标算法求解认知参数优化问题

柴争义1,3, 王秉2, 李亚伦1, 朱思峰4, 王颖锋5   

  1. 1. 天津工业大学计算机科学与软件学院 天津 300384;
    2. 河南交通职业技术学院航运海事系 河南郑州 450005;
    3. 泛网无线通信教育部重点实验室(北京邮电大学), 北京 100876;
    4. 周口师范学院数学与统计学院, 河南周口 466001;
    5. 河南财经政法大学计算机与信息工程学院, 河南郑州 450000
  • 收稿日期:2014-05-26 修回日期:2014-09-28 出版日期:2015-08-25 发布日期:2015-08-25
  • 通讯作者: 柴争义
  • 作者简介:王 秉 男,1965年出生,副教授,主要研究方向为无线网络、优化算法设计.
  • 基金资助:

    北京邮电大学泛网无线通信教育部重点实验室基金(No.KFKT-2013101);国家自然科学基金(No.U1204618,No.61202099);江苏省博士后科研资助(No.1202006C);中国博士后面上基金(No.2013M541586);河南省教育厅自然科学研究重点项目(No.13A520192);郑州市科技攻关项目(No.141PPTGG379)

Parameters Optimization of Cognitive Network Based on Artificial Physics Multi-Objective Algorithm

CHAI Zheng-yi1,3, WANG Bing2, LI Ya-lun1, ZHU Si-feng4, WANG Ying-feng5   

  1. 1. School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300384, China;
    2. Department of Maritime, Henan Vocational and Technical College of Communications, Zhengzhou, Henan 450005, China;
    3. Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    4. School of Mathematics and Statistics, Zhoukou Normal University, Zhoukou, Henan 466001, China;
    5. College of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou, Henan 450000, China
  • Received:2014-05-26 Revised:2014-09-28 Online:2015-08-25 Published:2015-08-25

摘要:

针对认知无线网络中的引擎参数调整问题,提出了一种基于拟态物理学多目标优化的求解算法.根据认知参数编码的二进制特点,设计了基于海明距离的个体排序方法,并改进了微粒的更新方程,最后求出问题的Pareto最优解集.多载波环境下的仿真实验表明,算法可以根据无线信道环境的动态变化和认知用户需求的不同需求,自适应调整各个子载波的调制方式和发射功率,满足参数优化需求.

关键词: 拟态物理学, 多目标优化, 认知无线电网络, 参数配置

Abstract:

To solve the engine parameter adjustment problem of cognitive radio networks, an artificial physics multi-objective optimization algorithm was proposed.According to its binary encoded features of cognitive parameters, Hamming distance based individual ranking method was designed and particle updated equation was improved, and finally the Pareto optimal set were achieved.Simulation results show that under the multi-carrier environment, the proposed algorithm can adjust transmission power and modulation mode according to the changing of channel and cognitive user demands.So it meets the demands for parameters optimization.

Key words: artificial physics, multi-objective optimization, cognitive engine, parameters adjustments

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