Reinforcement learning infused MAC for adaptive connectivity

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dc.authorscopusidKorhan Cengiz / 56522820200
dc.authorwosidKorhan Cengiz / HTN-8060-2023
dc.contributor.authorSah, Dinesh Kumar
dc.contributor.authorNauman, Ali
dc.contributor.authorJamshed, Muhammad Ali
dc.contributor.authorCengiz, Korhan
dc.contributor.authorIvković, Nikola
dc.contributor.authorUroš, Vedran
dc.date.accessioned2025-04-18T10:26:52Z
dc.date.available2025-04-18T10:26:52Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractThe beginning of cellular communication (next-gen, such as 5G and 6G) promises an extreme leap in connectivity, introducing intelligent, adaptive solutions that integrate communication, artificial intelligence, and emerging technologies. Our approach combines reinforcement learning with Medium Access Control (MAC) protocols to dynamically optimize resource allocation and enhance network performance. In this work, we explore the integration of the adaptive frame size adjusting approach similar to the IEEE 802.1CB to ensure the efficient handling of seamless redundancy. The proposed solutions are validated through simulation, ensuring robustness and real-world applicability. Results indicate significant improvements in redundancy rate detection and delay in the network. This work contributes to achieving intelligent, adaptive, and seamless connectivity in the next generation of communication systems.
dc.identifier.citationKumar Sah, D., Nauman, A., Jamshed, M. A., Cengiz, K., Ivkovic, N., & Uros, V. (2024). Reinforcement Learning Infused MAC for Adaptive Connectivity. In IEEE Wireless Communications and Networking Conference (IEEE WCNC), APR 21-24, 2024, Dubai, U ARAB EMIRATES. IEEE.
dc.identifier.doi10.1109/WCNC57260.2024.10571273
dc.identifier.isbn979-835030358-2
dc.identifier.issn15253511
dc.identifier.scopus2-s2.0-85198850011
dc.identifier.urihttp://dx.doi.org/10.1109/WCNC57260.2024.10571273
dc.identifier.urihttps://hdl.handle.net/20.500.12713/7073
dc.identifier.wosWOS:001268569304100
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorCengiz, Korhan
dc.institutionauthoridKorhan Cengiz / 0000-0001-6594-8861
dc.language.isoen
dc.publisherInstitute of electrical and electronics engineers inc.
dc.relation.ispartofIEEE wireless communications and networking conference, WCNC
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectConnectivity
dc.subjectIoT
dc.subjectMAC
dc.subjectReinforcement Learning
dc.subjectResource Utilization
dc.titleReinforcement learning infused MAC for adaptive connectivity
dc.typeConference Object

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