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dc.contributor.authorLahmeri, Mohamed-Amine
dc.contributor.authorA.Kishk, Mustafa
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2021-04-25T09:41:51Z
dc.date.available2021-04-25T09:41:51Z
dc.date.issued2021
dc.identifier.citationLahmeri, M.-A., A.Kishk, M., & Alouini, M.-S. (2021). Artificial Intelligence for UAV-enabled Wireless Networks: A Survey. IEEE Open Journal of the Communications Society, 1–1. doi:10.1109/ojcoms.2021.3075201
dc.identifier.issn2644-125X
dc.identifier.doi10.1109/OJCOMS.2021.3075201
dc.identifier.urihttp://hdl.handle.net/10754/668913
dc.description.abstractUnmanned 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.
dc.publisherIEEE
dc.relation.urlhttps://ieeexplore.ieee.org/document/9411810/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9411810/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9411810
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 License.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence
dc.subjectDeep learning
dc.subjectFederated learning
dc.subjectMachine learning
dc.subjectReinforcement learning
dc.subjectUAVs.
dc.titleArtificial Intelligence for UAV-enabled Wireless Networks: A Survey
dc.typeArticle
dc.contributor.departmentKing Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalIEEE Open Journal of the Communications Society
dc.eprint.versionPublisher's Version/PDF
kaust.personLahmeri, Mohamed-Amine
kaust.personA.Kishk, Mustafa
kaust.personAlouini, Mohamed-Slim
refterms.dateFOA2021-04-25T09:45:50Z


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