Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback

Al-Asadi, Ahmed; Al-Saedi, Ibtesam R. K.; Alwane, Saddam K.; Li, Hongxiang; Alzubaidi, Laith

doi:10.3390/s23187965

Open AccessArticle

Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback

by

Ahmed Al-Asadi

¹,

Ibtesam R. K. Al-Saedi

^1,2,

Saddam K. Alwane

¹,

Hongxiang Li

^2,* and

Laith Alzubaidi

^3,4

¹

Communication Engineering Department, University of Technology, Baghdad P.O. Box 19006, Iraq

²

Electrical and Computer Engineering Department, University of Louisville, Louisville, KY 40292, USA

³

School of Mechanical Medical and Process Engineering, Queensland University of Technology, Brisbane 4000, QLD, Australia

⁴

Centre for Data Science, Queensland University of Technology, Brisbane 4000, QLD, Australia

^*

Author to whom correspondence should be addressed.

Sensors 2023, 23(18), 7965; https://doi.org/10.3390/s23187965

Submission received: 27 July 2023 / Revised: 31 August 2023 / Accepted: 7 September 2023 / Published: 19 September 2023

(This article belongs to the Special Issue MIMO Technologies in Sensors and Wireless Communication Applications)

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Abstract

Multiple Input and Multiple Output (MIMO) is a promising technology to enable spatial multiplexing and improve throughput in wireless communication networks. To obtain the full benefits of MIMO systems, the Channel State Information (CSI) should be acquired correctly at the transmitter side for optimal beamforming design. The analytical centre-cutting plane method (ACCPM) has shown to be an appealing way to obtain the CSI at the transmitter side. This paper adopts ACCPM to learn down-link CSI in both single-user and multi-user scenarios. In particular, during the learning phase, it uses the null space beamforming vector of the estimated CSI to reduce the power usage, which approaches zero when the learned CSI approaches the optimal solution. Simulation results show our proposed method converges and outperforms previous studies. The effectiveness of the proposed method was corroborated by applying it to the scattering channel and winner II channel models.

Keywords: MIMO; CSI; beamforming; ACCPM; downlink; channel model; Gram–Schmidt process

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MDPI and ACS Style

Al-Asadi, A.; Al-Saedi, I.R.K.; Alwane, S.K.; Li, H.; Alzubaidi, L. Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback. Sensors 2023, 23, 7965. https://doi.org/10.3390/s23187965

AMA Style

Al-Asadi A, Al-Saedi IRK, Alwane SK, Li H, Alzubaidi L. Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback. Sensors. 2023; 23(18):7965. https://doi.org/10.3390/s23187965

Chicago/Turabian Style

Al-Asadi, Ahmed, Ibtesam R. K. Al-Saedi, Saddam K. Alwane, Hongxiang Li, and Laith Alzubaidi. 2023. "Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback" Sensors 23, no. 18: 7965. https://doi.org/10.3390/s23187965

APA Style

Al-Asadi, A., Al-Saedi, I. R. K., Alwane, S. K., Li, H., & Alzubaidi, L. (2023). Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback. Sensors, 23(18), 7965. https://doi.org/10.3390/s23187965

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Enhanced MIMO CSI Estimation Using ACCPM with Limited Feedback

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