Lahmeri, Mohamed-Amine and Kishk, Mustafa A. and Alouini, Mohamed-Slim (2021) Artificial Intelligence for UAV-Enabled Wireless Networks: A Survey. IEEE Open Journal of the Communications Society, 2. pp. 1015-1040. ISSN 2644-125X

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Abstract

Unmanned aerial vehicles (UAVs) are considered as one of the promising technologies for the next-generation wireless communication networks. Their mobility and their ability to establish line of sight (LOS) links with the users made them key solutions for many potential applications. In the same vein, artificial intelligence (AI) is growing rapidly nowadays and has been very successful, particularly due to the massive amount of the available data. As a result, a significant part of the research community has started to integrate intelligence at the core of UAVs networks by applying AI algorithms in solving several problems in relation to drones. In this article, we provide a comprehensive overview of some potential applications of AI in UAV-based networks. We also highlight the limits of the existing works and outline some potential future applications of AI for UAVs networks.

Item Type:	Article
Keywords:	Artificial intelligence; deep learning; federated learning; machine learning; reinforcement learning; UAVs;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	16974
Identification Number:	https://doi.org/10.1109/OJCOMS.2021.3075201
Depositing User:	Mustafa Kishk
Date Deposited:	28 Feb 2023 15:29
Journal or Publication Title:	IEEE Open Journal of the Communications Society
Publisher:	IEEE Open Journal of the Communications Society
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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