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

Xuanfan Shen; Yong Liao; Xuewu Dai

doi:10.1109/GlobalSIP.2018.8646337

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

Xuanfan Shen, Yong Liao, Xuewu Dai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 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 language	English
Title of host publication	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
Publisher	IEEE
Pages	1214-1217
Number of pages	4
ISBN (Electronic)	9781728112954
ISBN (Print)	9781728112961
DOIs	https://doi.org/10.1109/GlobalSIP.2018.8646337
Publication status	Published - 21 Feb 2019
Event	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Anaheim, United States Duration: 26 Nov 2018 → 29 Nov 2018

Conference

Conference	2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
Country/Territory	United States
City	Anaheim
Period	26/11/18 → 29/11/18

Keywords

5G-enabled V2V channel
BEM
Channel estimation
Non-stationary channel
UKF

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10.1109/GlobalSIP.2018.8646337

Cite this

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title = "BEM-based UKF channel estimation for 5G-enabled V2V channel",

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.",

keywords = "5G-enabled V2V channel, BEM, Channel estimation, Non-stationary channel, UKF",

author = "Xuanfan Shen and Yong Liao and Xuewu Dai",

year = "2019",

month = feb,

day = "21",

doi = "10.1109/GlobalSIP.2018.8646337",

language = "English",

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pages = "1214--1217",

booktitle = "2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings",

publisher = "IEEE",

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note = "2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 ; Conference date: 26-11-2018 Through 29-11-2018",

}

Shen, X, Liao, Y & Dai, X 2019, BEM-based UKF channel estimation for 5G-enabled V2V channel. in 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings. IEEE, pp. 1214-1217, 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018, Anaheim, United States, 26/11/18. https://doi.org/10.1109/GlobalSIP.2018.8646337

TY - GEN

T1 - BEM-based UKF channel estimation for 5G-enabled V2V channel

AU - Shen, Xuanfan

AU - Liao, Yong

AU - Dai, Xuewu

PY - 2019/2/21

Y1 - 2019/2/21

N2 - 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.

AB - 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.

KW - 5G-enabled V2V channel

KW - BEM

KW - Channel estimation

KW - Non-stationary channel

KW - UKF

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U2 - 10.1109/GlobalSIP.2018.8646337

DO - 10.1109/GlobalSIP.2018.8646337

M3 - Conference contribution

AN - SCOPUS:85063108535

SN - 9781728112961

SP - 1214

EP - 1217

BT - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

PB - IEEE

T2 - 2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018

Y2 - 26 November 2018 through 29 November 2018

ER -

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

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Keywords

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