Citation

Elijah, Olakunle and Abdul Rahim, Sharul Kamal and New, Wee Kiat and Leow, Chee Yen and Cumanan, Kanapathippillai and Tan, Kim Geok (2022) Intelligent Massive MIMO Systems for Beyond 5G Networks: An Overview and Future Trends. IEEE Access, 10. pp. 102532-102563. ISSN 2169-3536

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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:	Modulation, Artificial neural networks, 5G mobile communication, Wireless networks, Market research, 6G mobile communication, Uplink, MIMO communication, Machine learning
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	31 Oct 2022 07:39
Last Modified:	31 Oct 2022 07:39
URII:	http://shdl.mmu.edu.my/id/eprint/10589

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