Multi-antenna Arrays Based Massive-MIMO for B5G/6G: State-of-the-Art, Challenges and Future Research Directions

Faizan Qamar; Syed Hussain Ali Kazmi; Khairul Akram Zainol Ariffin; Muhammad Tayyab; Quang Ngoc Nguyen

doi:10.20944/preprints202406.0197.v1

Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 3 June 2024 / Approved: 4 June 2024 / Online: 4 June 2024 (16:27:56 CEST)

This comprehensive article explores Massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, Cell-Free MIMO, and security considerations, the article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of Federated Learning in M-MIMO systems. By examining these cutting-edge developments, the article aims to contribute to advancing knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

5G; 6G; M-MIMO; Multi-Antenna; Wireless; Federated Learning

Engineering, Telecommunications

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Multi-antenna Arrays Based Massive-MIMO for B5G/6G: State-of-the-Art, Challenges and Future Research Directions

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