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

作     者：Linghui Zeng Fuqiang Yao Jianzhao Zhang Min Jia Linghui Zeng;Fuqiang Yao;Jianzhao Zhang;Min Jia

作者机构：The Sixty-third Research InstituteNational University of Defense TechnologyNanjing 210007China Communication Research CenterSchool of Electronics and Information EngineeringHarbin Institute of TechnologyHarbin 150080China 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2022年第19卷第7期

页      面：13-24页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：supported by National Natural Science Foundation of China (No. 62131005) 

主　　题：prior knowledge reinforcement learning anti-jamming communication spectrum access 

摘      要：The spectrum access problem of cognitive users in the fast-changing dynamic interference spectrum environment is addressed in this *** prior knowledge for the dynamic spectrum access is modeled and a reliability quantification scheme is presented to guide the use of the prior knowledge in the learning ***,a spectrum access 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 electromagnetic *** 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 *** results show that,the convergence speed of the learning is improved by about 66%with the invariant average throughput.