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    Machine learning for UAV-Based networks

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    Type
    Preprint
    Authors
    Lahmeri, Mohamed-Amine
    Kishk, Mustafa Abdelsalam cc
    Alouini, Mohamed-Slim cc
    KAUST Department
    Communication Theory Lab
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2020-09-24
    Permanent link to this record
    http://hdl.handle.net/10754/665445
    
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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 a line of sight (LOS) links with the users made them key solutions for many potential applications. In the same vein, artificial intelligence 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 machine learning (ML) algorithms in solving several problems in relation to drones. In this article, we provide a comprehensive overview of some potential applications of ML in UAV-Based networks. We will also highlight the limits of the existing works and outline some potential future applications of ML for UAVs networks.
    Publisher
    arXiv
    arXiv
    2009.11522
    Additional Links
    https://arxiv.org/pdf/2009.11522
    Collections
    Preprints; Electrical and Computer Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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