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：08[工学] 081105[工学-导航、制导与控制] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0814[工学-土木工程] 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 surge.However,harsh and dynamic marine communication environmentcan distort transmission signal,which significantly weaken the communication performance.Therefore,for maritime wireless communication system,the channel estimation is often required to detect the channel suffered from the impacts of changing factors.Since 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 distribution.This paper studies the radio channel estimation problem of wireless communications over the sea surface.To 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 error.By the aid of MAB,the estimation is not only dynamic according to channel variation,but also does not need to know the channel distribution.Simulation results show that the proposed algorithm can achieve higher estimation accuracy compared to matching pursuit(MP)-based and fractional Fourier transform(FrFT)-based methods.