Adaptive Channel Estimation Scheme Based on LTE Uplink in V2V Environments

Jihye Lee, Sangmi Moon, Soonho Kwon, Myeonghun Chu, Sara Bae, Cheolwoo You, Huaping Liu, Jeong Ho Kim, Dae Jin Kim, Hosung Park, Jin Young Kim, Intae Hwang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Vehicle communication can facilitate efficient coordination among vehicles on the road and enable future vehicular applications such as vehicle safety enhancement, infotainment, or even autonomous driving. In the 3rd Generation Partnership Project (3GPP), many studies focus on long term evolution (LTE)-based vehicle communication. Because vehicle communication is closely related to safety, it requires low latency and improved reliability. However, vehicle speed is high enough to cause severe channel distortion in vehicle-to-vehicle (V2V) environments. We can utilize channel estimation methods to approach a reliable vehicle communication systems. Conventional channel estimation schemes can be categorized as least-squares (LS), decision-directed channel estimation (DDCE), spectral temporal averaging (STA), and smoothing methods. In this study, we propose a smart channel estimation scheme in LTE-based V2V environments. The channel estimation scheme, based on an LTE uplink system, uses a demodulation reference signal (DMRS) as the pilot symbol. Unlike conventional channel estimation schemes, we propose an adaptive smoothing channel estimation scheme (ASCE) using quadratic smoothing (QS) of the pilot symbols, which estimates a channel with greater accuracy and adaptively estimates channels in data symbols. In simulation results, the proposed ASCE scheme shows improved overall performance in terms of the normalized mean square error (NMSE) and bit error rate (BER) relative to conventional schemes.

Original languageEnglish
Pages (from-to)383-398
Number of pages16
JournalWireless Personal Communications
Volume102
Issue number1
DOIs
StatePublished - 1 Sep 2018

Bibliographical note

Funding Information:
Acknowledgements This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-R2718-16-0011) supervised by the IITP (Institute for Information and communications Technology Promotion). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01059397). This study was financially supported by Chonnam National University (Grant Number: 2016-2503).

Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • ASCE
  • DDCE
  • LTE
  • QS
  • STA
  • Smoothing
  • V2V

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