Resource allocation in 5G cloud-RAN using deep reinforcement learning algorithms: A review

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dc.authoridsadr, mohammad mohsen/0000-0002-4309-1948
dc.authoridSohrabi, Mohammad Karim/0000-0001-8066-0356
dc.authorwosidsadr, mohammad mohsen/IWL-8189-2023
dc.authorwosidjamali, shahram/F-4862-2017
dc.authorwosidSohrabi, Mohammad Karim/AAD-8618-2019
dc.contributor.authorKhani, Mohsen
dc.contributor.authorJamali, Shahram
dc.contributor.authorSohrabi, Mohammad Karim
dc.contributor.authorSadr, Mohammad Mohsen
dc.contributor.authorGhaffari, Ali
dc.date.accessioned2024-05-19T14:50:25Z
dc.date.available2024-05-19T14:50:25Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThis paper reviews recent research on resource allocation in 5G cloud-based radio access networks (C-RAN) using deep reinforcement learning (DRL) algorithms. It explores the potential of DRL for learning complex decision-making policies without human intervention. The paper first introduces the C-RAN architecture and resource allocation concepts, followed by an overview of DRL algorithms applied to C-RAN. It discusses the challenges and potential solutions in applying DRL to C-RAN resource allocation, including scalability, convergence, and fairness. The review concludes by highlighting open research directions for future investigation. By providing insights into the state-of-the-art techniques for resource allocation in 5G C-RAN using DRL, this paper emphasizes their potential impact on advancing 5G network technology.en_US
dc.identifier.doi10.1002/ett.4929
dc.identifier.issn2161-3915
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85180894313en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org10.1002/ett.4929
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5702
dc.identifier.volume35en_US
dc.identifier.wosWOS:001135111200001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofTransactions on Emerging Telecommunications Technologiesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectJoint Optimizationen_US
dc.subjectC-Ranen_US
dc.subjectComputational Resourcesen_US
dc.subjectRadioen_US
dc.subjectNetworksen_US
dc.subjectMachineen_US
dc.subjectAccessen_US
dc.subjectNomaen_US
dc.subjectFrameworken_US
dc.subjectSecurityen_US
dc.titleResource allocation in 5G cloud-RAN using deep reinforcement learning algorithms: A reviewen_US
dc.typeReview Articleen_US

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