BEM-based UKF Channel Estimation for 5G-enabled V2V Channel

Shen, Xuanfan, Liao, Yong and Dai, Xuewu (2019) BEM-based UKF Channel Estimation for 5G-enabled V2V Channel. In: 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, pp. 1214-1217. ISBN 978-1-7281-1296-1

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/GlobalSIP.2018.8646337

Abstract

An Unscented Kalman Filter (UKF) based on Basis Expansion Model (BEM) is proposed in this paper to cope with the challenges of 5G-enabled V2V channel estimation. The BEM is adopted to reduce the estimation complexity and eliminate the inter-carrier interference (ICI). A channel estimation based on UKF which is able to jointly estimate the time-varying time correlation coefficients and channel impulse response (CIR) in a non-linear state space model is proposed. Simulation results illustrate that the proposed BEM-based UKF method shows better estimation accuracy, robustness and bit error rate (BER) performance than the traditional channel estimation methods in 5G-enabled V2V channel.

Item Type: Book Section
Uncontrolled Keywords: 5G-enabled V2V channel, non-stationary channel, channel estimation, BEM, UKF
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 14:54
Last Modified: 10 Oct 2019 18:31
URI: http://nrl.northumbria.ac.uk/id/eprint/39510

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