Xuanfan Shen, Yong Liao, X. Dai, Daotong Li, Kai Liu
{"title":"BEM-based EKF-RTSS Channel Estimation for Non-stationary Doubly-selective Channel","authors":"Xuanfan Shen, Yong Liao, X. Dai, Daotong Li, Kai Liu","doi":"10.1109/ICCCHINA.2018.8641253","DOIUrl":null,"url":null,"abstract":"An extended Kalman filter and Rauch-Tung-Striebel Smoother (EKF-RTSS) based on Basis Expansion Model (BEM) is proposed in this paper to cope with the challenges of doubly-selective and non-stationary channel in high-speed environments. For doubly-selective channel, the BEM is adopted to reduce the estimation complexity. For non-stationary channel, a channel estimation based on EKF which is able to jointly estimate the time-varying time correlation coefficients and channel impulse response (CIR) is proposed. For further improving the channel estimation accuracy, a ‘filtering and smoothing’ channel estimator structure is designed by introducing the RTSS into channel estimation and interpolation. Simulation results illustrate that the proposed BEM-based EKF-RTSS method show better estimation accuracy, robustness and bit error rate (BER) performance than the traditional methods in high-speed scenarios.","PeriodicalId":170216,"journal":{"name":"2018 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE/CIC International Conference on Communications in China (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCHINA.2018.8641253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
An extended Kalman filter and Rauch-Tung-Striebel Smoother (EKF-RTSS) based on Basis Expansion Model (BEM) is proposed in this paper to cope with the challenges of doubly-selective and non-stationary channel in high-speed environments. For doubly-selective channel, the BEM is adopted to reduce the estimation complexity. For non-stationary channel, a channel estimation based on EKF which is able to jointly estimate the time-varying time correlation coefficients and channel impulse response (CIR) is proposed. For further improving the channel estimation accuracy, a ‘filtering and smoothing’ channel estimator structure is designed by introducing the RTSS into channel estimation and interpolation. Simulation results illustrate that the proposed BEM-based EKF-RTSS method show better estimation accuracy, robustness and bit error rate (BER) performance than the traditional methods in high-speed scenarios.