A Survey on Machine-Learning Techniques for UAV-Based Communications

Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new de...

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Veröffentlicht in:Sensors (Basel, Switzerland) Switzerland), 2019-11, Vol.19 (23), p.5170
Hauptverfasser: Bithas, Petros S, Michailidis, Emmanouel T, Nomikos, Nikolaos, Vouyioukas, Demosthenes, Kanatas, Athanasios G
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Sprache:eng
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Zusammenfassung:Unmanned aerial vehicles (UAVs) will be an integral part of the next generation wireless communication networks. Their adoption in various communication-based applications is expected to improve coverage and spectral efficiency, as compared to traditional ground-based solutions. However, this new degree of freedom that will be included in the network will also add new challenges. In this context, the machine-learning (ML) framework is expected to provide solutions for the various problems that have already been identified when UAVs are used for communication purposes. In this article, we provide a detailed survey of all relevant research works, in which ML techniques have been used on UAV-based communications for improving various design and functional aspects such as channel modeling, resource management, positioning, and security.
ISSN:1424-8220
1424-8220
DOI:10.3390/s19235170