Fast Subspace-based Semi-Blind Channel Estimation for MIMO-OFDM Communications

Kabiru N. Aliyu*, Abdulmajid Lawal*, Karim Abed-Meraim, Azzedine Zerguine*

*Corresponding author for this work

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

Abstract

This work addresses the issue of semi-blind (SB) subspace-based channel estimation when MIMO-OFDM communications systems are considered. The suggested solution primarily decreases the computational cost while ensuring reliable channel estimates. Covariance matrices and noise subspace are calculated for each subcarrier in a parallel manner by utilizing the OFDM modulation's orthogonality property. Pilots and data are then jointly used in a SB scheme, via a global (hybrid) cost function, to improve further the channel estimation accuracy as well as the information data throughput. To support our study, several numerical simulations are performed to investigate the requirements for channel identifiability and assess the performance and limitations of our SB method.

Original languageEnglish
Title of host publication31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages1460-1463
Number of pages4
ISBN (Electronic)9789464593600
DOIs
StatePublished - 2023
Event31st European Signal Processing Conference, EUSIPCO 2023 - Helsinki, Finland
Duration: 4 Sep 20238 Sep 2023

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Conference

Conference31st European Signal Processing Conference, EUSIPCO 2023
Country/TerritoryFinland
CityHelsinki
Period4/09/238/09/23

Bibliographical note

Publisher Copyright:
© 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

Keywords

  • MIMO
  • OFDM
  • semi-blind channel estimation
  • subspace method

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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