[1]郑志刚,薛菲,周井泉.网络效益最大化的认知无线电频谱分配算法[J].计算机技术与发展,2013,(08):91-94.
 ZHENG Zhi-gang,XUE Fei,ZHOU Jing-quan.Cognitive Radio Spectrum Assignment Algorithm with Network Benefit Maximization[J].,2013,(08):91-94.
点击复制

网络效益最大化的认知无线电频谱分配算法()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2013年08期
页码:
91-94
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Cognitive Radio Spectrum Assignment Algorithm with Network Benefit Maximization
文章编号:
1673-629X(2013)08-0091-04
作者:
郑志刚薛菲周井泉
南京邮电大学 电子科学与工程学院
Author(s):
ZHENG Zhi-gangXUE FeiZHOU Jing-quan
关键词:
认知无线电频谱分配小生境自适应遗传算法
Keywords:
cognitive radiospectrum allocationNicheself-adaptiongenetic algorithm
文献标志码:
A
摘要:
首先介绍了认知无线电系统中频谱分配的图论着色模型。针对该模型以网络效益最大化为目标,设计了自适应的交叉和变异算子,并在此基础上引入小生境技术,提出了基于自适应小生境遗传算法的认知无线电频谱分配算法。通过仿真实验比较了本算法、颜色敏感图论算法与经典遗传算法的性能。结果表明基于自适应小生境的遗传算法不易陷入局部最优,在较少的代数内就可以找到理想最优解,能更好地实现网络频谱效益最大化,其性能优于颜色敏感图论算法和经典遗传算法
Abstract:
Firstly introduce the graph coloring model of spectrum allocation in cognitive radio system. According to this model,design self-adptive crossover and mutation operator with the network benefit maximization as the goal. Based on it,Niche technology is introduced. Then cognitive radio spectrum assignment based on self-adaptive Niche genetic algorithm is proposed. Simulations are conducted to com-pare the proposed method with color sensitive graph coloring algorithm and classical genetic algorithm. Results show that the proposed method cannot easily trap into local optimum,and can find the optimal solutions after only several generations,what is more,it better opti-mizes network spectrum utilization. The proposed method greatly outperforms the color sensitive graph coloring algorithm and classical genetic algorithm

相似文献/References:

[1]林琳 周贤伟 薛楠 刘臻臻.认知无线电网络安全路由问题研究[J].计算机技术与发展,2010,(01):155.
 LIN Lin,ZHOU Xian-wei,XUE Nan,et al.Study on Problems of Security Routing in Cognitive Radio Networks[J].,2010,(08):155.
[2]孙丽艳.基于激励机制的认知无线电自私行为研究[J].计算机技术与发展,2009,(10):170.
 SUN Li-yan.Study of Cognitive Radio' Selfish Behavior Based on Two- Stage Incentives Mechanism[J].,2009,(08):170.
[3]郭云玮 刘全 高俊.不同衰落信道下的协作感知性能研究[J].计算机技术与发展,2011,(05):13.
 GUO Yun-wei,LIU Quan,GAO Jun.Performance of Cooperative Spectrum Sensing over Different Fading Channels[J].,2011,(08):13.
[4]任长城 马雏.智能家居中基于认知无线电的通信协议设计[J].计算机技术与发展,2011,(08):14.
 REN Chang-cheng,MA Chu.A Design of Cognitive Radio Communication Protocol in Smart Home[J].,2011,(08):14.
[5]汪晓睿 刘全.认知无线电网络中频谱感知安全的研究进展[J].计算机技术与发展,2011,(12):155.
 WANG Xiao-rui,LIU Quan.A Survey on Spectrum Sensing Security Issues in Cognitive Radio Networks[J].,2011,(08):155.
[6]宗平 刘柳 乔秀泉[].认知无线电技术在ZigBee中的应用研究[J].计算机技术与发展,2012,(08):241.
 ZONG Ping,LIU Liu,QIAO Xiu-quan.Application Research of Cognitive Radio Technology in ZigBee[J].,2012,(08):241.
[7]王韦刚 胡海峰.基于压缩感知的协作频谱检测[J].计算机技术与发展,2012,(12):241.
 WANG Wei-gang,HU Hai-feng.Collaborative Spectrum Detection Based on Compressed Sensing[J].,2012,(08):241.
[8]刘洋,季薇,侯晓赟.一种改进的基于 OMP 重建的宽带频谱感知算法[J].计算机技术与发展,2013,(01):99.
 LIU Yang,JI Wei,HOU Xiao-yun.A Modified Spectrum Sensing Algorithm for Wideband Cognitive Radio Based on OMP[J].,2013,(08):99.
[9]赵之旭,田峰.一种改进的认知无线电功率控制博弈算法[J].计算机技术与发展,2013,(02):101.
 ZHAO Zhi-xu,TIAN Feng.An Improved Power Control Game Algorithm in Cognitive Radios[J].,2013,(08):101.
[10]黄德文,周井泉.基于价格的认知网络频谱共享博弈论模型[J].计算机技术与发展,2013,(08):66.
 HUANG De-wen,ZHOU Jing-quan.Cognitive Network Spectrum Sharing Game Theory Model Based on Price[J].,2013,(08):66.
[11]孔小丽,周井泉.基于用户需求的改进型频谱资源分配算法[J].计算机技术与发展,2013,(03):73.
 KONG Xiao-li,ZHOU Jing-quan.Advanced Spectrum Resource Allocation Algorithm Based on User Requirement[J].,2013,(08):73.
[12]岳文静,孙 鹏,陈 志.基于改进海鸥算法的认知无人机网络频谱分配[J].计算机技术与发展,2021,31(09):7.[doi:10. 3969 / j. issn. 1673-629X. 2021. 09. 002]
 YUE Wen-jing,SUN Peng,CHEN Zhi.Spectrum Allocation of Cognitive UAV Network Based on Improved Seagull Algorithm[J].,2021,31(08):7.[doi:10. 3969 / j. issn. 1673-629X. 2021. 09. 002]
[13]张金飞,岳文静,陈 志.基于改进麻雀搜索算法的认知无线电频谱分配[J].计算机技术与发展,2023,33(01):95.[doi:10. 3969 / j. issn. 1673-629X. 2023. 01. 015]
 ZHANG Jin-fei,YUE Wen-jing,CHEN Zhi.Spectrum Allocation of Cognitive Radio Based on Improved Sparrow Search Algorithm[J].,2023,33(08):95.[doi:10. 3969 / j. issn. 1673-629X. 2023. 01. 015]

更新日期/Last Update: 1900-01-01