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dc.contributor.authorVenkateswararao, Kunaen
dc.contributor.authorSwain, Pravatien
dc.contributor.authorChristophorou, Christophorosen
dc.contributor.authorPitsillides, Andreasen
dc.coverage.spatialIndiaen
dc.creatorVenkateswararao, Kunaen
dc.creatorSwain, Pravatien
dc.creatorChristophorou, Christophorosen
dc.creatorPitsillides, Andreasen
dc.date.accessioned2021-01-22T10:47:41Z
dc.date.available2021-01-22T10:47:41Z
dc.date.issued2019
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/62388
dc.description.abstractThe 5G cellular network is the new generation of mobile networks that will play a key role in supporting current and forthcoming demands for wireless access by various devices in an Ultradense network. Small Cells is the most encouraging technological feature of the 5G. This paper builds on the idea of the User Equipment-based Virtual Base Station (UE-VBS) concept that enhances the Smartphones of the general population into Virtual Small Base Stations, referred as eligible-UEs, and embeds them in the Mobile Network Infrastructure. Part of these eligible-UEs are activated on the-fly into UE-VBSs to support the network infrastructure in stressful or overloaded situations in Ultra-dense 5G networks. To process the initial connection between the client UEs and eligible-UEs, the Initializing Matching Connection Algorithm (IMCA) is implemented based on the SINR preference of the client UEs to eligible-UEs. The IMCA algorithm results in the formation of clusters. The proposed Virtual Small Cell (VSC) activation algorithm optimizes the clusters based on the upper and lower bound constraints on the size of the cluster, which results in the formation of UE-VBS. The IMCA and VSC activation algorithms are implemented in MATLAB, and the results are validated using the NS3 networking simulator.en
dc.source2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)en
dc.titleDynamic selection of Virtual Small Base Station in 5G Ultra-Dense Network using Initializing Matching Connection Algorithmen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/ANTS47819.2019.9118045
dc.description.startingpage1
dc.description.endingpage6
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.contributor.orcidPitsillides, Andreas [0000-0001-5072-2851]
dc.gnosis.orcid0000-0001-5072-2851


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