An Adaptive Genetic Based Cognitive Radio Parameter Adjustment Algorithm

A. Sun, Tao Liang, Yajun Zhang, Wei Lu
{"title":"An Adaptive Genetic Based Cognitive Radio Parameter Adjustment Algorithm","authors":"A. Sun, Tao Liang, Yajun Zhang, Wei Lu","doi":"10.1109/ISCID.2014.203","DOIUrl":null,"url":null,"abstract":"To overcome the drawbacks such as pre-maturity and the inclination to converge to partial optimum of the standard genetic algorithm, the adaptive genetic algorithm has been proposed in this paper. The adaptive genetic algorithm can change its cross-over probability and mutation probability adaptively according to the iterative times and the value of the cost function to avoid the shortcomings of the standard genetic algorithm. The paper also analyses the dynamic reconfiguration problem in the cognitive radio system which is a key aspect in realizing the optimization of wireless resources management. At last, the proposed algorithm is simulated under three different modes of the OFDM multi-carrier system. The simulation results indicate that the adaptive genetic algorithm can overcome the drawbacks of the standard genetic algorithm effectively, the parameters adjustment outcomes coincide with the expected results.","PeriodicalId":385391,"journal":{"name":"2014 Seventh International Symposium on Computational Intelligence and Design","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Seventh International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2014.203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

To overcome the drawbacks such as pre-maturity and the inclination to converge to partial optimum of the standard genetic algorithm, the adaptive genetic algorithm has been proposed in this paper. The adaptive genetic algorithm can change its cross-over probability and mutation probability adaptively according to the iterative times and the value of the cost function to avoid the shortcomings of the standard genetic algorithm. The paper also analyses the dynamic reconfiguration problem in the cognitive radio system which is a key aspect in realizing the optimization of wireless resources management. At last, the proposed algorithm is simulated under three different modes of the OFDM multi-carrier system. The simulation results indicate that the adaptive genetic algorithm can overcome the drawbacks of the standard genetic algorithm effectively, the parameters adjustment outcomes coincide with the expected results.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于自适应遗传的认知无线电参数调整算法
为了克服标准遗传算法的早熟和倾向于收敛到部分最优的缺点,本文提出了自适应遗传算法。自适应遗传算法可以根据迭代次数和代价函数的取值自适应地改变其交叉概率和突变概率,避免了标准遗传算法的不足。本文还分析了认知无线电系统中的动态重构问题,这是实现无线资源管理优化的关键。最后,对该算法在OFDM多载波系统的三种不同模式下进行了仿真。仿真结果表明,自适应遗传算法能有效克服标准遗传算法的缺点,参数调整结果与预期结果吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An Integrated Framework for Analysis and Mining of the Massive Sensor Data Using Feature Preserving Strategy on Cloud Computing Acetylene Density Measurement System Based on Differential and Harmonic Detection Research Intelligent Fire Evacuation System Based on Ant Colony Algorithm and MapX Research on the Application of Intelligent Campus Supermarket System -- Based on the Internet of Things (IOT) Technology Speaker Recognition Method Based on CPSO Clustering and KMP Algorithm
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1