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Intelligent massive MIMO systems for beyond 5G networks: An overview and future trends

Elijah, Olakunle and Abdul Rahim, Sharul Kamal and Wee, Kiat New and Chee, Yen Leow and Cumanan, Kanapathippilla and Tan, Kim Geok (2022) Intelligent massive MIMO systems for beyond 5G networks: An overview and future trends. IEEE Access, 10 (NA). pp. 102532-102563. ISSN 2169-3536

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Official URL: http://dx.doi.org/10.1109/ACCESS.2022.3208284

Abstract

Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the potential of challenging large-scale problems in conventional massive multiple-input-multiple-output (CM-MIMO) systems. This introduces the concept of intelligent massive MIMO (I-mMIMO) systems. Due to the surge of application of different ML techniques in the enhancement of mMIMO systems for existing and emerging use cases beyond fifth-generation (B5G) networks, this article aims to provide an overview of the different aspects of the I-mMIMO systems. First, the characteristics and challenges of the CM-MIMO have been identified. Secondly, the most recent efforts aimed at applying ML to a different aspect of CM-MIMO systems are presented. Thirdly, the deployment of I-mMIMO and efforts towards standardization are discussed. Lastly, the future trends of I-mMIMO-enabled application systems are presented. The aim of this paper is to assist the readers to understand different ML approaches in CM-MIMO systems, explore some of the advantages and disadvantages, identify some of the open issues, and motivate the readers toward future trends.

Item Type:Article
Uncontrolled Keywords:5G, 6G network, artificial intelligence, beyond 5G, deep learning, intelligent MIMO, machine learning, massive MIMO
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:104423
Deposited By: Widya Wahid
Deposited On:04 Feb 2024 09:58
Last Modified:04 Feb 2024 09:58

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