Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/62908
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dc.contributor.authorJaffry, Shanen
dc.contributor.authorZaidi, Syeda Kanwalen
dc.contributor.authorShah, Syed Tariqen
dc.contributor.authorHasan, Syed Farazen
dc.contributor.authorGui, Xiangen
dc.date.accessioned2024-09-18T03:32:06Z-
dc.date.available2024-09-18T03:32:06Z-
dc.date.issued2019-
dc.identifier.citationProceedings of the International Conference on Communications, ICC 2019, p. 1-6en
dc.identifier.isbn9781538680889en
dc.identifier.issn1938-1883en
dc.identifier.urihttps://hdl.handle.net/1959.11/62908-
dc.description.abstract<p>In order to enhance the capacity of the Fifth Generation and beyond (5GB) cellular networks, third generation partnership project (3GPP) has provided guidelines for enabling device-to-device (D2D) communication. An essential requirement for successful D2D communication is the users' ability to discover each other, specially in the out-of-network scenarios. While there has been some research effort in the area of D2D discovery, most of the works assume that the devices are static. In a typical mobile environment, the constraints like time-to-discovery, etc, are more rigid and deserve investigation. This paper formulates a mathematical model for a mobile device's neighborhood discovery as it moves across an area that has other D2D users. In particular, we determine the expected number of users discovered by a mobile device while moving in a straight line between two way-points following random waypoint mobility. The model is verified using Monte-Carlo simulation and can be used for future analysis of mobile D2D-discovery.</p>en
dc.languageenen
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.relation.ispartofProceedings of the International Conference on Communications, ICC 2019en
dc.titleD2D Neighborhood Discovery by a Mobile Deviceen
dc.typeConference Publicationen
dc.relation.conferenceICC 2019: IEEE International Conference on Communicationsen
dc.identifier.doi10.1109/ICC.2019.8761940en
local.contributor.firstnameShanen
local.contributor.firstnameSyeda Kanwalen
local.contributor.firstnameSyed Tariqen
local.contributor.firstnameSyed Farazen
local.contributor.firstnameXiangen
local.profile.schoolResearch Servicesen
local.profile.emailshasan3@une.edu.auen
local.output.categoryE1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.date.conference20th - 24th May, 2019en
local.conference.placeShanghai, Chinaen
local.publisher.placeUnited States of Americaen
local.format.startpage1en
local.format.endpage6en
local.peerreviewedYesen
local.contributor.lastnameJaffryen
local.contributor.lastnameZaidien
local.contributor.lastnameShahen
local.contributor.lastnameHasanen
local.contributor.lastnameGuien
dc.identifier.staffune-id:shasan3en
local.profile.orcid0009-0006-5345-2790en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/62908en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleD2D Neighborhood Discovery by a Mobile Deviceen
local.output.categorydescriptionE1 Refereed Scholarly Conference Publicationen
local.conference.detailsICC 2019: IEEE International Conference on Communications, Shanghai, China, 20th - 24th May, 2019en
local.search.authorJaffry, Shanen
local.search.authorZaidi, Syeda Kanwalen
local.search.authorShah, Syed Tariqen
local.search.authorHasan, Syed Farazen
local.search.authorGui, Xiangen
local.uneassociationNoen
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2019en
local.subject.for20204006 Communications engineeringen
local.subject.seo2020tbden
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-09-18en
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