BEM-based EKF-RTSS Channel Estimation for Non-stationary Doubly-selective Channel

Shen, Xuanfan, Liao, Yong, Dai, Xuewu, Li, Daotong and Liu, Kai (2019) BEM-based EKF-RTSS Channel Estimation for Non-stationary Doubly-selective Channel. In: 2018 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, pp. 536-541. ISBN 978-1-5386-7006-4

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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.

Item Type: Book Section
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Becky Skoyles
Date Deposited: 05 Jun 2019 15:03
Last Modified: 10 Oct 2019 18:31

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