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
PDF
3MB |
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 |
Repository Staff Only: item control page