Qazzaz, M.M.H. orcid.org/0000-0002-7048-2960, Zaidi, S.A.R., McLernon, D.C. et al. (3 more authors) (2024) Non-Terrestrial UAV Clients for Beyond 5G Networks: A Comprehensive Survey. Ad Hoc Networks, 157. 103440. ISSN 1570-8705
Abstract
The rapid proliferation of consumer UAVs, or drones, is reshaping the wireless communication landscape. These agile, autonomous devices find new life as UE in cellular networks. This paper explores their integration, emphasizing the myriad applications, standardization efforts, challenges, and research community solutions. Key areas of investigation include the complexities of 3D deployment, channel modelling, and energy efficiency. Moreover, we highlight the open questions and research opportunities these flying UEs present. The evolving landscape of UAV integration into cellular networks promises transformative enhancements for next-generation communications, addressing challenges while fostering innovation across industries. The paper encapsulates the essential aspects of UAV integration within the cellular ecosystem, offering a concise yet comprehensive overview of this dynamic field, where UAVs as UEs redefine wireless communication with promise and complexity.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by Elsevier. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Cellular-connected UAVs; UAVs; 5G/6G; Machine Learning; Reinforcement Learning; Aerial user equipment; 3GPP; Next-generation communications; Non-terrestrial networks |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 27 Feb 2024 14:14 |
Last Modified: | 27 Feb 2024 14:14 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.adhoc.2024.103440 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209662 |