Modelling and enhanced scheduling in the cellular vehicular sidelink standards
dc.contributor.advisor | O'Driscoll, Aisling | |
dc.contributor.advisor | Sreenan, Cormac J. | |
dc.contributor.author | McCarthy, Brian | en |
dc.contributor.funder | Science Foundation Ireland | en |
dc.date.accessioned | 2024-05-29T08:12:39Z | |
dc.date.available | 2024-05-29T08:12:39Z | |
dc.date.issued | 2024 | |
dc.date.submitted | 2024 | |
dc.description.abstract | Vehicular networking can address significant challenges in the areas of vehicular safety, traffic efficiency, and enables higher levels of autonomous driving for sustainable mobility. The Third Generation Partnership Project (3GPP) Cellular Vehicle-To-Everything (C-V2X) standard and subsequent New Radio Vehicle-To-Everything (NR-V2X) standard are relatively new yet disruptive technology enablers in the regulatory landscape. Unfortunately, the relative infancy of the standards has resulted in shortcomings in their ability to effectively handle real-life vehicular service characteristics and network management techniques. Specifically, the scheduler that forms the basis of both C-V2X and NR-V2X cannot effectively schedule variable packet inter arrival rates, variable packet sizes or facilitate congestion control techniques. This thesis will address these challenges by providing a rigorous analysis of the scheduling problems caused by these contemporary vehicular applications, emphasising the complexity posed by European Telecommunications Standards Institute (ETSI) and 3GPP standard application models. It further addresses the pressing issue of congestion management within diverse and dense vehicular scenarios, all while preserving scheduling performance. Specifically, this thesis proposes, evaluates, and analyses solutions based on machine learning enabled prediction of inter packet arrival times, scheduler compliant congestion control mechanisms, and a deep understanding of the role of MCS adaptation in V2X scheduling. | en |
dc.description.status | Not peer reviewed | en |
dc.description.version | Accepted Version | en |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | McCarthy, B. 2024. Modelling and enhanced scheduling in the cellular vehicular sidelink standards. PhD Thesis, University College Cork. | |
dc.identifier.endpage | 215 | |
dc.identifier.uri | https://hdl.handle.net/10468/15938 | |
dc.language.iso | en | en |
dc.publisher | University College Cork | en |
dc.relation.project | info:eu-repo/grantAgreement/SFI/SFI Research Centres Programme/17/RC-PhD/3479/IE/CONNECT PhD Recruitment Scheme/ | |
dc.rights | © 2024, Brian McCarthy. | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | Vehicular networking | |
dc.subject | NR-V2X | |
dc.subject | C-V2X | |
dc.subject | SB-SPS | |
dc.subject | Mode4 | |
dc.subject | Mode2 | |
dc.subject | 3GPP | |
dc.subject | Cooperative awareness | |
dc.title | Modelling and enhanced scheduling in the cellular vehicular sidelink standards | |
dc.type | Doctoral thesis | en |
dc.type.qualificationlevel | Doctoral | en |
dc.type.qualificationname | PhD - Doctor of Philosophy | en |
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