Channel estimation based on multi-armed approach for maritime OFDM wireless communications

作     者：Zhang Qianqian Xu Yanli Zhang Qianqian;Xu Yanli

作者机构：College of Information EngineeringShanghai Maritime UniversityShanghai 201306China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2023年第30卷第4期

页      面：75-85,120页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 081505[工学-港口、海岸及近海工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0810[工学-信息与通信工程] 081105[工学-导航、制导与控制] 0815[工学-水利工程] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 0824[工学-船舶与海洋工程] 081001[工学-通信与信息系统] 0814[工学-土木工程] 082401[工学-船舶与海洋结构物设计制造] 0811[工学-控制科学与工程] 

基　　金：supported by the Natural Science Foundation Project of Shanghai(20ZR1423200) the Innovation Program of Shanghai Municipal Education Commission(2021-01-07-00-10-E00121) 

主　　题：maritime wireless communications channel estimation multi-armed bandit 

摘      要：With the development of maritime informatization and the increased generation of marine data,the demands of efficient and reliable maritime communication ***,harsh and dynamic marine communication environmentcan distort transmission signal,which significantly weaken the communication ***,for maritime wireless communication system,the channel estimation is often required to detect the channel suffered from the impacts of changing *** there is no universal maritime communication channel model and channel varies dynamically,channel estimation method needs to make decision dynamically without pre-knowledge of channel *** paper studies the radio channel estimation problem of wireless communications over the sea *** improve the estimation accuracy,this paper utilizes multi-armed bandit(MAB)problem to deal with the uncertainty of channel state information(CSI),then proposes a dynamic channel estimation algorithm to explore the global changing channel information,and asymptotically minimize the estimation *** the aid of MAB,the estimation is not only dynamic according to channel variation,but also does not need to know the channel *** results show that the proposed algorithm can achieve higher estimation accuracy compared to matching pursuit(MP)-based and fractional Fourier transform(FrFT)-based methods.