Basis Expansion Extrapolation Based DL Channel Prediction with UL Channel Estimates for TDD MIMO-OTFS Systems

Yanfeng Zhang*, Xu Zhu*, Yujie Liu, Yufei Jiang*, Ruibin Yin, Yong Liang Guan, G. David González

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Orthogonal time frequency space (OTFS) modulation has become an effective technique for high-mobility scenarios. However, its performance could be severely degraded due to channel aging caused by user mobility and high processing latency. In this paper, an integrated scheme of uplink (UL) channel estimation and downlink (DL) channel prediction is proposed to alleviate channel aging in time division duplex (TDD) multi-input multi-output (MIMO) OTFS systems. Specifically, first, an iterative data-aided channel estimation scheme is proposed to accurately acquire UL channels with the aid of specifically designed frame pattern. Then the discrete prolate spheroidal basis expansion model (DPS-BEM) is used to model the time-varying UL channel estimates, and the dynamic DPS-BEM coefficients are fitted by a set of orthogonal polynomials. A channel predictor is derived to predict DL channels for all antenna pairs and paths by iteratively extrapolating the fitting coefficients. Simulation results verify that the proposed scheme outperforms the existing schemes in terms of normalized mean square error of channel prediction and DL sum-rate.

Original languageEnglish
Title of host publicationICC 2023 - IEEE International Conference on Communications
Subtitle of host publicationSustainable Communications for Renaissance
EditorsMichele Zorzi, Meixia Tao, Walid Saad
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2270-2275
Number of pages6
ISBN (Electronic)9781538674628
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2023 IEEE International Conference on Communications, ICC 2023 - Rome, Italy
Duration: May 28 2023Jun 1 2023

Publication series

NameIEEE International Conference on Communications
Volume2023-May
ISSN (Print)1550-3607

Conference

Conference2023 IEEE International Conference on Communications, ICC 2023
Country/TerritoryItaly
CityRome
Period5/28/236/1/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus Subject Areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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