Blind MMSE Equalizer for Nonlinear SIMO Systems

Abdulmajid Lawal; Karim Abed-Meraim; Qadri Mayyala; Navid Iqbal; Azzedine Zerguine

doi:10.1109/SSD52085.2021.9429382

Blind MMSE Equalizer for Nonlinear SIMO Systems

Abdulmajid Lawal, Karim Abed-Meraim, Qadri Mayyala, Navid Iqbal, Azzedine Zerguine

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

3 Scopus citations

Abstract

This work presents a novel minimum mean squared error (MMSE) equalizer for blind signal estimation of a nonlinear single input multiple outputs (SIMO) system. The zero and \tau delay MMSE equalizer parameters are blindly estimated using the property that they belong to both the signal subspace and the kernel of a properly truncated data covariance matrix. Moreover, in the proposed approach, an appropriate demixing technique is employed to get rid of the inherent ambiguity to the equalized signal in such a nonlinear context. Numerical simulations show that the proposed MMSE blind SIMO nonlinear estimation exhibits a promising performance at a relatively low computational cost.

Original language	English
Title of host publication	18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	510-513
Number of pages	4
ISBN (Electronic)	9781665414937
DOIs	https://doi.org/10.1109/SSD52085.2021.9429382
State	Published - 22 Mar 2021

Publication series

Name	18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

MMSE
SIMO
blind equalizer
nonlinear

ASJC Scopus subject areas

Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Signal Processing
Electrical and Electronic Engineering

Access to Document

10.1109/SSD52085.2021.9429382

Cite this

Lawal, A., Abed-Meraim, K., Mayyala, Q., Iqbal, N., & Zerguine, A. (2021). Blind MMSE Equalizer for Nonlinear SIMO Systems. In 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021 (pp. 510-513). Article 9429382 (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSD52085.2021.9429382

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abstract = "This work presents a novel minimum mean squared error (MMSE) equalizer for blind signal estimation of a nonlinear single input multiple outputs (SIMO) system. The zero and \tau delay MMSE equalizer parameters are blindly estimated using the property that they belong to both the signal subspace and the kernel of a properly truncated data covariance matrix. Moreover, in the proposed approach, an appropriate demixing technique is employed to get rid of the inherent ambiguity to the equalized signal in such a nonlinear context. Numerical simulations show that the proposed MMSE blind SIMO nonlinear estimation exhibits a promising performance at a relatively low computational cost.",

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author = "Abdulmajid Lawal and Karim Abed-Meraim and Qadri Mayyala and Navid Iqbal and Azzedine Zerguine",

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Lawal, A, Abed-Meraim, K, Mayyala, Q, Iqbal, N & Zerguine, A 2021, Blind MMSE Equalizer for Nonlinear SIMO Systems. in 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021., 9429382, 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021, Institute of Electrical and Electronics Engineers Inc., pp. 510-513. https://doi.org/10.1109/SSD52085.2021.9429382

Blind MMSE Equalizer for Nonlinear SIMO Systems. / Lawal, Abdulmajid; Abed-Meraim, Karim; Mayyala, Qadri et al.
18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 510-513 9429382 (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021).

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

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AU - Lawal, Abdulmajid

AU - Abed-Meraim, Karim

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N2 - This work presents a novel minimum mean squared error (MMSE) equalizer for blind signal estimation of a nonlinear single input multiple outputs (SIMO) system. The zero and \tau delay MMSE equalizer parameters are blindly estimated using the property that they belong to both the signal subspace and the kernel of a properly truncated data covariance matrix. Moreover, in the proposed approach, an appropriate demixing technique is employed to get rid of the inherent ambiguity to the equalized signal in such a nonlinear context. Numerical simulations show that the proposed MMSE blind SIMO nonlinear estimation exhibits a promising performance at a relatively low computational cost.

AB - This work presents a novel minimum mean squared error (MMSE) equalizer for blind signal estimation of a nonlinear single input multiple outputs (SIMO) system. The zero and \tau delay MMSE equalizer parameters are blindly estimated using the property that they belong to both the signal subspace and the kernel of a properly truncated data covariance matrix. Moreover, in the proposed approach, an appropriate demixing technique is employed to get rid of the inherent ambiguity to the equalized signal in such a nonlinear context. Numerical simulations show that the proposed MMSE blind SIMO nonlinear estimation exhibits a promising performance at a relatively low computational cost.

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Lawal A, Abed-Meraim K, Mayyala Q, Iqbal N , Zerguine A. Blind MMSE Equalizer for Nonlinear SIMO Systems. In 18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 510-513. 9429382. (18th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2021). doi: 10.1109/SSD52085.2021.9429382

Blind MMSE Equalizer for Nonlinear SIMO Systems

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

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