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dc.contributor.authorChen, Jun
dc.contributor.authorChang, Zheng
dc.contributor.authorGuo, Wenlong
dc.contributor.authorGuo, Xijuan
dc.date.accessioned2022-08-25T10:01:40Z
dc.date.available2022-08-25T10:01:40Z
dc.date.issued2022
dc.identifier.citationChen, J., Chang, Z., Guo, W., & Guo, X. (2022). Resource Allocation and Computation Offloading for Wireless Powered Mobile Edge Computing. <i>Sensors</i>, <i>22</i>(16), Article 6002. <a href="https://doi.org/10.3390/s22166002" target="_blank">https://doi.org/10.3390/s22166002</a>
dc.identifier.otherCONVID_151675760
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/82820
dc.description.abstractIn this paper, we investigate a resource allocation and computation offloading problem in a heterogeneous mobile edge computing (MEC) system. In the considered system, a wireless power transfer (WPT) base station (BS) with an MEC sever is able to deliver wireless energy to the mobile devices (MDs), and the MDs can utilize the harvested energy for local computing or task offloading to the WPT BS or a Macro BS (MBS) with a stronger computing server. In particular, we consider that the WPT BS can utilize full- or half-duplex wireless energy transmission mode to empower the MDs. The aim of this work focuses on optimizing the offloading decision, full/half-duplex energy harvesting mode and energy harvesting (EH) time allocation with the objective of minimizing the energy consumption of the MDs. As the formulate problem has a non-convex mixed integer programming structure, we use the quadratically constrained quadratic program (QCQP) and semi-definite relaxation (SDR) methods to solve it. The simulation results demonstrate the effectiveness of the proposed scheme.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherMDPI AG
dc.relation.ispartofseriesSensors
dc.rightsCC BY 4.0
dc.subject.othermobile edge computing
dc.subject.otheroffloading
dc.subject.otherwireless power transfer
dc.subject.otherfull-duplex
dc.subject.otherhalf-duplex
dc.titleResource Allocation and Computation Offloading for Wireless Powered Mobile Edge Computing
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202208254353
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineSecure Communications Engineering and Signal Processingfi
dc.contributor.oppiaineTekniikkafi
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineSecure Communications Engineering and Signal Processingen
dc.contributor.oppiaineEngineeringen
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn1424-8220
dc.relation.numberinseries16
dc.relation.volume22
dc.type.versionpublishedVersion
dc.rights.copyright© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
dc.rights.accesslevelopenAccessfi
dc.subject.ysoallokointi
dc.subject.ysomobiililaitteet
dc.subject.ysolangaton tiedonsiirto
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p1033
jyx.subject.urihttp://www.yso.fi/onto/yso/p4834
jyx.subject.urihttp://www.yso.fi/onto/yso/p5445
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.3390/s22166002
jyx.fundinginformationThis research was funded by Innovation Capability Improvement Plan Project of Hebei Province of funder grant number 22567626H.
dc.type.okmA1


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