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Neighbor-Aware Non-Orthogonal Multiple Access Scheme for Energy Harvesting Internet of Things

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dc.contributor.authorKim, Yumi-
dc.contributor.authorPaik, Mincheol-
dc.contributor.authorKim, Bokyeong-
dc.contributor.authorKo, Haneul-
dc.contributor.authorKim, Seung-Yeon-
dc.date.accessioned2022-06-11T10:40:28Z-
dc.date.available2022-06-11T10:40:28Z-
dc.date.created2022-06-10-
dc.date.issued2022-01-
dc.identifier.issn1424-8220-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/141997-
dc.description.abstractIn a non-orthogonal multiple access (NOMA) environment, an Internet of Things (IoT) device achieves a high data rate by increasing its transmission power. However, excessively high transmission power can cause an energy outage of an IoT device and have a detrimental effect on the signal-to-interference-plus-noise ratio of neighbor IoT devices. In this paper, we propose a neighbor-aware NOMA scheme (NA-NOMA) where each IoT device determines whether to transmit data to the base station and the transmission power at each time epoch in a distributed manner with the consideration of its energy level and other devices' transmission powers. To maximize the aggregated data rate of IoT devices while keeping an acceptable average energy outage probability, a constrained stochastic game model is formulated, and the solution of the model is obtained using a best response dynamics-based algorithm. Evaluation results show that NA-NOMA can increase the average data rate up to 22% compared with a probability-based scheme while providing a sufficiently low energy outage probability (e.g., 0.05).-
dc.languageEnglish-
dc.language.isoen-
dc.publisherMDPI-
dc.subjectRESOURCE-ALLOCATION-
dc.subjectPOWER ALLOCATION-
dc.subjectNOMA-
dc.subjectOPTIMIZATION-
dc.subjectNETWORKS-
dc.titleNeighbor-Aware Non-Orthogonal Multiple Access Scheme for Energy Harvesting Internet of Things-
dc.typeArticle-
dc.contributor.affiliatedAuthorKo, Haneul-
dc.identifier.doi10.3390/s22020448-
dc.identifier.scopusid2-s2.0-85122251291-
dc.identifier.wosid000758709800001-
dc.identifier.bibliographicCitationSENSORS, v.22, no.2-
dc.relation.isPartOfSENSORS-
dc.citation.titleSENSORS-
dc.citation.volume22-
dc.citation.number2-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryChemistry, Analytical-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordPlusRESOURCE-ALLOCATION-
dc.subject.keywordPlusPOWER ALLOCATION-
dc.subject.keywordPlusNOMA-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusNETWORKS-
dc.subject.keywordAuthorgame theory-
dc.subject.keywordAuthorconstrained stochastic game-
dc.subject.keywordAuthorenergy-
dc.subject.keywordAuthorenergy harvesting-
dc.subject.keywordAuthorInternet of Things (IoT)-
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