BEM-based UKF channel estimation for 5G-enabled V2V channel

Xuanfan Shen, Yong Liao, Xuewu Dai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1214-1217
Number of pages4
ISBN (Electronic)9781728112954
ISBN (Print)9781728112961
DOIs
Publication statusPublished - 21 Feb 2019
Event2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Anaheim, United States
Duration: 26 Nov 201829 Nov 2018

Conference

Conference2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
CountryUnited States
CityAnaheim
Period26/11/1829/11/18

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