Overview of machine learning approaches for wireless communication

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Machine learning is one of the most popular research areas, and it is commonly used in wireless communications and networks. Security and fast communication are among of the key requirements for next generation wireless networks. Machine learning techniques are getting more important day-by-day since the types, amount, and structure of data is continuously changing. Recent developments in smart phones and other devices like drones, wearable devices, machines with sensors need reliable communication within internet of things (IoT) systems. For this purpose, artificial intelligence can increase the security and reliability and manage the data that is generated by the wireless systems. In this chapter, the authors investigate several machine learning techniques for wireless communications including deep learning, which represents a branch of artificial neural networks. Copyright © 2021, IGI Global.

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AlanDeğerDil
dc.contributor.authorEnsari, Tolga
dc.contributor.authorGünay, Melike
dc.contributor.authorNalçakan, Yağiz
dc.contributor.authorYildiz, Eyyüp
dc.date.accessioned2026-10-18T20:28:18.668413401Z
dc.date.available2026-10-18T20:28:18.668413401Z
dc.date.issued2020
dc.description.abstractMachine learning is one of the most popular research areas, and it is commonly used in wireless communications and networks. Security and fast communication are among of the key requirements for next generation wireless networks. Machine learning techniques are getting more important day-by-day since the types, amount, and structure of data is continuously changing. Recent developments in smart phones and other devices like drones, wearable devices, machines with sensors need reliable communication within internet of things (IoT) systems. For this purpose, artificial intelligence can increase the security and reliability and manage the data that is generated by the wireless systems. In this chapter, the authors investigate several machine learning techniques for wireless communications including deep learning, which represents a branch of artificial neural networks. Copyright © 2021, IGI Global.
dc.identifier.doi10.4018/978-1-7998-7705-9.ch069
dc.identifier.endpage1597
dc.identifier.isbn978-179987748-6; 978-179987705-9
dc.identifier.scopus2-s2.0-85163989112
dc.identifier.startpage1579
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/13474
dc.identifier.volume3-4
dc.language.isoen
dc.publisherIGI Global
dc.relation.ispartofResearch Anthology on Artificial Intelligence Applications in Security
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleOverview of machine learning approaches for wireless communication
dc.typeBook Chapter
dspace.entity.typePublication
rdl.citation.scopus0
rdl.source.indexSCOPUS