Dynamic Spectrum Access Based on Prior Knowledge Enabled Reinforcement Learning with Double Actions in Complex Electromagnetic Environment|Linghui Zeng;Fuqiang Yao;Jianzhao Zhang;Min Jia|Communication Research Center,School of Electronics and Information Engineering,Harbin Institute of Technology,Harbin 150080,China - 期刊导航|首站-论文投稿智能助手|论文发表|论文智能投稿|期刊自助发表推荐|杂志社快速发表|查同导刊-域田数据官方网站

典型文献

Dynamic Spectrum Access Based on Prior Knowledge Enabled Reinforcement Learning with Double Actions in Complex Electromagnetic Environment

文献摘要：

The spectrum access problem of cogni-tive users in the fast-changing dynamic interference spectrum environment is addressed in this paper. The prior knowledge for the dynamic spectrum access is modeled and a reliability quantification scheme is pre-sented to guide the use of the prior knowledge in the learning process. Furthermore, a spectrum ac-cess scheme based on the prior knowledge enabled RL (PKRL) is designed, which effectively improved the learning efficiency and provided a solution for users to better adapt to the fast-changing and high-density elec-tromagnetic environment. Compared with the existing methods, the proposed algorithm can adjust the access channel online according to historical information and improve the efficiency of the algorithm to obtain the optimal access policy. Simulation results show that, the convergence speed of the learning is improved by about 66％with the invariant average throughput.

文献关键词：

中图分类号：

[1] 自动化技术、计算机技术（TP） / 计算技术、计算机技术（TP3） / 计算机的应用（TP39） / 信息处理(信息加工)（TP391）

[2] 天文学、地球科学（P） / 地球物理学（P3） / 空间物理（P35）

[3] 医药、卫生（R） / 基础医学（R3） / 病理学（R36） / 病理过程（R364）

作者姓名：

Linghui Zeng;Fuqiang Yao;Jianzhao Zhang;Min Jia

作者机构：

The Sixty-third Research Institute,National University of Defense Technology,Nanjing 210007,China;Communication Research Center,School of Electronics and Information Engineering,Harbin Institute of Technology,Harbin 150080,China

文献出处：

中国通信（英文版）

引用格式：

[1]Linghui Zeng;Fuqiang Yao;Jianzhao Zhang;Min Jia-.Dynamic Spectrum Access Based on Prior Knowledge Enabled Reinforcement Learning with Double Actions in Complex Electromagnetic Environment)[J].中国通信（英文版）,2022(07):13-24

A类：

PKRL

B类：

Dynamic,Spectrum,Access,Based,Prior,Knowledge,Enabled,Reinforcement,Learning,Double,Actions,Complex,Electromagnetic,Environment,spectrum,access,problem,cogni,users,fast,changing,dynamic,interference,environment,addressed,this,paper,prior,knowledge,modeled,reliability,quantification,scheme,pre,sented,guide,learning,process,Furthermore,enabled,designed,which,effectively,improved,efficiency,provided,solution,better,adapt,high,density,elec,Compared,existing,methods,proposed,algorithm,can,adjust,channel,online,according,historical,information,obtain,optimal,policy,Simulation,results,show,that,convergence,speed,by,about,invariant,average,throughput

AB值：

0.587864

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