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

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

doi:10.23919/EUSIPCO58844.2023.10289965

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 proceeding › Conference contribution › peer-review

1 Scopus citations

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 language	English
Title of host publication	31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings
Publisher	European Signal Processing Conference, EUSIPCO
Pages	1460-1463
Number of pages	4
ISBN (Electronic)	9789464593600
DOIs	https://doi.org/10.23919/EUSIPCO58844.2023.10289965
State	Published - 2023
Event	31st European Signal Processing Conference, EUSIPCO 2023 - Helsinki, Finland Duration: 4 Sep 2023 → 8 Sep 2023

Publication series

Name	European Signal Processing Conference
ISSN (Print)	2219-5491

Conference

Conference	31st European Signal Processing Conference, EUSIPCO 2023
Country/Territory	Finland
City	Helsinki
Period	4/09/23 → 8/09/23

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

Access to Document

10.23919/EUSIPCO58844.2023.10289965

Cite this

Aliyu, K. N., Lawal, A., Abed-Meraim, K., & Zerguine, A. (2023). Fast Subspace-based Semi-Blind Channel Estimation for MIMO-OFDM Communications. In 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings (pp. 1460-1463). (European Signal Processing Conference). European Signal Processing Conference, EUSIPCO. https://doi.org/10.23919/EUSIPCO58844.2023.10289965

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title = "Fast Subspace-based Semi-Blind Channel Estimation for MIMO-OFDM Communications",

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.",

keywords = "MIMO, OFDM, semi-blind channel estimation, subspace method",

author = "Aliyu, {Kabiru N.} and Abdulmajid Lawal and Karim Abed-Meraim and Azzedine Zerguine",

note = "Publisher Copyright: {\textcopyright} 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.; 31st European Signal Processing Conference, EUSIPCO 2023 ; Conference date: 04-09-2023 Through 08-09-2023",

year = "2023",

doi = "10.23919/EUSIPCO58844.2023.10289965",

language = "English",

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Aliyu, KN, Lawal, A, Abed-Meraim, K & Zerguine, A 2023, Fast Subspace-based Semi-Blind Channel Estimation for MIMO-OFDM Communications. in 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. European Signal Processing Conference, European Signal Processing Conference, EUSIPCO, pp. 1460-1463, 31st European Signal Processing Conference, EUSIPCO 2023, Helsinki, Finland, 4/09/23. https://doi.org/10.23919/EUSIPCO58844.2023.10289965

Fast Subspace-based Semi-Blind Channel Estimation for MIMO-OFDM Communications. / Aliyu, Kabiru N.; Lawal, Abdulmajid; Abed-Meraim, Karim et al.
31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. European Signal Processing Conference, EUSIPCO, 2023. p. 1460-1463 (European Signal Processing Conference).

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

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T1 - Fast Subspace-based Semi-Blind Channel Estimation for MIMO-OFDM Communications

AU - Aliyu, Kabiru N.

AU - Lawal, Abdulmajid

AU - Abed-Meraim, Karim

AU - Zerguine, Azzedine

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N2 - 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.

AB - 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.

KW - MIMO

KW - OFDM

KW - semi-blind channel estimation

KW - subspace method

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BT - 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings

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

Abstract

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Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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