Distributed Online Handover Decisions for Energy Efficiency in Dense HetNets
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song,Yujae | - |
dc.contributor.author | Lim,Sung Hoon | - |
dc.contributor.author | Jeon,Sang-Woon | - |
dc.date.accessioned | 2023-09-04T05:35:40Z | - |
dc.date.available | 2023-09-04T05:35:40Z | - |
dc.date.issued | 2020-12 | - |
dc.identifier.issn | 2334-0983 | - |
dc.identifier.issn | 2576-6813 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114652 | - |
dc.description.abstract | In this paper, we consider the problem of handover decision making in the context of a dense heterogeneous network with a macro base station and multiple small base stations. We propose a distributed deep Q-learning based algorithm that minimizes the overall energy consumption by taking into account both the energy consumption from transmission and hand over overheads. The proposed algorithm is performed in a distributed and interactive manner in which a centralized training agent manages the replay buffer for training its deep Q-network, by gathering state, action, and reward information reported from distributed handover agents. We perform several numerical evaluations and demonstrate that the proposed algorithm provides 10% to 30% energy savings over other contemporary handover mechanisms depending on handover overhead costs. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | IEEE | - |
dc.title | Distributed Online Handover Decisions for Energy Efficiency in Dense HetNets | - |
dc.type | Article | - |
dc.publisher.location | 미국 | - |
dc.identifier.doi | 10.1109/GLOBECOM42002.2020.9348215 | - |
dc.identifier.scopusid | 2-s2.0-85101268829 | - |
dc.identifier.wosid | 000668970505043 | - |
dc.identifier.bibliographicCitation | GLOBECOM 2020 - 2020 IEEE Global Communications Conference, v.2020-January, pp 1 - 6 | - |
dc.citation.title | GLOBECOM 2020 - 2020 IEEE Global Communications Conference | - |
dc.citation.volume | 2020-January | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 6 | - |
dc.type.docType | Proceedings Paper | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/9348215?arnumber=9348215&SID=EBSCO:edseee | - |
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