Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/32129
Title: Enhanced SPS Velocity-Adaptive Scheme: Access Fairness in 5G NR V2I Networks
Authors: Xu, X
Wu, Q
Fan, P
Wang, K
Keywords: 5G NR V2I;SPS;fairness access
Issue Date: 23-May-2025
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Xu, X. et al. (2025) 'Enhanced SPS Velocity-Adaptive Scheme: Access Fairness in 5G NR V2I Networks', 2025 IEEE International Workshop on Radio Frequency and Antenna Technologies (iWRF&AT), Shenzhen, China, 23-26 May, pp. 294 - 299. doi: 10.1109/iWRFAT65352.2025.11102889.
Abstract: Vehicle-to-Infrastructure (V2I) technology enables information exchange between vehicles and road infrastructure. Specifically, when a vehicle approaches a roadside unit (RSU), it can exchange information with the RSU to obtain accurate data that assists in driving. As the 3rd Generation Partnership Project (3GPP) Release 16, which includes the 5G New Radio (NR) Vehicle-to-Everything (V2X) standards, vehicles typically adopt mode- 2 communication using sensing-based semi-persistent scheduling (SPS). By this approach, vehicles identify resources through a selection window and exclude ineligible resources based on information from a sensing window. However, vehicles often drive at different speeds, resulting in varying amounts of data transmission with RSUs as they pass by, which leads to unfair access. Therefore, developing an scheme that accounts for different vehicle speeds to achieve fair access across the network is essential. This paper formulates an optimization problem for vehicular environment and proposes a multi-objective optimization scheme to address it by adjusting the selection window size. Experimental results validate the efficiency of the proposed method.
URI: https://bura.brunel.ac.uk/handle/2438/32129
DOI: https://doi.org/10.1109/iWRFAT65352.2025.11102889
ISBN: 979-8-3315-4422-5 (ebk)
ISSN: 979-8-3315-4423-2 (PoD)
Other Identifiers: ORCiD: Kezhi Wang https://orcid.org/0000-0001-8602-0800
Appears in Collections:Dept of Computer Science Research Papers

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