Joint channel estimation and decoding design for 5G-enabled V2V channel

Xuanfan Shen; Yong Liao; Xuewu Dai; Ming Zhao; Kai Liu; Dan Wang

doi:10.1109/CC.2018.8424581

Joint channel estimation and decoding design for 5G-enabled V2V channel

Xuanfan Shen, Yong Liao^*, Xuewu Dai, Ming Zhao, Kai Liu, Dan Wang

^*Corresponding author for this work

Mathematics, Physics and Electrical Engineering

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular (V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing (OFDM) system, we perform extended Kalman filter (EKF) for channel estimation in conjunction with Iterative Detector Decoder (IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.

Original language	English
Pages (from-to)	39-46
Number of pages	8
Journal	China Communications
Volume	15
Issue number	7
Early online date	2 Aug 2018
DOIs	https://doi.org/10.1109/CC.2018.8424581
Publication status	E-pub ahead of print - 2 Aug 2018

Keywords

extended Kalman filter (EKF)
Iterative Detector Decoder (IDD)
non-stationary channel estimation
orthogonal frequency division multiplexing (OFDM)
vehicular-to-vehicular (V2V)

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10.1109/CC.2018.8424581

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title = "Joint channel estimation and decoding design for 5G-enabled V2V channel",

abstract = "This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular (V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing (OFDM) system, we perform extended Kalman filter (EKF) for channel estimation in conjunction with Iterative Detector Decoder (IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.",

keywords = "extended Kalman filter (EKF), Iterative Detector Decoder (IDD), non-stationary channel estimation, orthogonal frequency division multiplexing (OFDM), vehicular-to-vehicular (V2V)",

author = "Xuanfan Shen and Yong Liao and Xuewu Dai and Ming Zhao and Kai Liu and Dan Wang",

year = "2018",

month = aug,

day = "2",

doi = "10.1109/CC.2018.8424581",

language = "English",

volume = "15",

pages = "39--46",

journal = "China Communications",

issn = "1673-5447",

publisher = "China Institute of Communication",

number = "7",

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TY - JOUR

T1 - Joint channel estimation and decoding design for 5G-enabled V2V channel

AU - Shen, Xuanfan

AU - Liao, Yong

AU - Dai, Xuewu

AU - Zhao, Ming

AU - Liu, Kai

AU - Wang, Dan

PY - 2018/8/2

Y1 - 2018/8/2

N2 - This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular (V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing (OFDM) system, we perform extended Kalman filter (EKF) for channel estimation in conjunction with Iterative Detector Decoder (IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.

AB - This paper addresses the problem of channel estimation in 5G-enabled vehicular-to-vehicular (V2V) channels with high-mobility environments and non-stationary feature. Considering orthogonal frequency division multiplexing (OFDM) system, we perform extended Kalman filter (EKF) for channel estimation in conjunction with Iterative Detector Decoder (IDD) at the receiver to improve the estimation accuracy. The EKF is proposed for jointly estimating the channel frequency response and the time-varying time correlation coefficients. And the IDD structure is adopted to reduce the estimation errors in EKF. The simulation results show that, compared with traditional methods, the proposed method effectively promotes the system performance.

KW - extended Kalman filter (EKF)

KW - Iterative Detector Decoder (IDD)

KW - non-stationary channel estimation

KW - orthogonal frequency division multiplexing (OFDM)

KW - vehicular-to-vehicular (V2V)

U2 - 10.1109/CC.2018.8424581

DO - 10.1109/CC.2018.8424581

M3 - Article

AN - SCOPUS:85051207819

SN - 1673-5447

VL - 15

SP - 39

EP - 46

JO - China Communications

JF - China Communications

IS - 7

ER -

Joint channel estimation and decoding design for 5G-enabled V2V channel

Abstract

Keywords

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