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Priority-Driven Resource Allocation with Reuse for Platooning in 5G Vehicular Network
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- Title
- Priority-Driven Resource Allocation with Reuse for Platooning in 5G Vehicular Network
- Issued Date
- 2025-02
- Citation
- Kim, Tae-Woo. (2025-02). Priority-Driven Resource Allocation with Reuse for Platooning in 5G Vehicular Network. Sustainability, 17(4). doi: 10.3390/su17041747
- Type
- Article
- Author Keywords
- 5G mobile communication ; vehicles ; resource allocation ; wireless channels ; automated driving & intelligent vehicles
- ISSN
- 2071-1050
- Abstract
-
Recently, Vehicle-to-Everything (V2X) communication has emerged as a critical technology for enhancing the safety and traffic management of autonomous vehicles. Developing a resource allocation algorithm that enables autonomous vehicles to perceive and react to their surroundings in real time through fast and reliable communication is of paramount importance. This paper proposes a novel resource allocation algorithm that minimizes the degradation of communication performance for non-platoon vehicles while ensuring low-latency, high-reliability communication within vehicle platoons. The proposed algorithm prioritizes platoon vehicles and enhances resource efficiency by simultaneously applying interference-based and distance-based resource reuse techniques. Performance evaluations conducted using the Simu5G simulator demonstrate that the proposed algorithm consistently maintains the average resource allocation rate and delay for both platoon and non-platoon vehicles, even as the number of platoons increases. Specifically, in a congested environment with 60 general vehicles and five platoons, the proposed algorithm achieves an average resource allocation rate of over 90%, significantly outperforming existing algorithms such as Max-C/I, which achieves only 58%, and the priority-based algorithm with 54%, ensuring reliable communication for all vehicles. © 2025 by the authors.
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- Publisher
- MDPI
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Related Researcher
- Park, Kyung-Joon박경준
-
Department of Electrical Engineering and Computer Science
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