Artificial Intelligence for UAV-Enabled Wireless Networks: A Survey

Искусственный интеллект для беспроводных сетей с использованием БПЛА: обзор
Mohamed-Slim Alouini, Mohamed-Amine Lahmeri, Mustafa A. Kishk
2021-01-01

AI for UAV networksArtificial intelligenceLine of sight (LOS) linksUAV-enabled wireless networksUnmanned aerial vehicles
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.
1
AI is increasingly integrated into UAV networks to solve various drone-related problems, leveraging massive available data.
2
The paper identifies limitations in existing works and outlines potential future AI applications for UAV networks.
3
The paper provides a comprehensive overview of potential AI applications in UAV-based networks.
4
UAVs are promising technologies for next-generation wireless networks due to mobility and ability to establish LOS links with users.

UAV-enabled wireless networks

Applications and integration of artificial intelligence techniques within UAV-enabled wireless networks, including AI-based solutions for mobility, LOS link management, and other network problems, plus limitations and future research directions

Publication Details
Publication Date
2021-01-01
Journal
Publisher
ISSN
Cited by
132
Access Type
Author Information
Authors
Mohamed-Slim Alouini
Mohamed-Amine Lahmeri
Mustafa A. Kishk
Explore further
Open the scid.ai AI chat with a ready-made request: it will find papers on a similar topic and help build a literature review.
Find similar papers in the chat
Make a presentation
100%