Ultra-Reliable Low-Latency Communications in Autonomous Vehicular Networks
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Abstract (arXiv)
Autonomous vehicles are expected to emerge as a main trend in vehicle development over the next decade. To support autonomous vehicles, ultra-reliable low-latency communications (URLLC) is required between autonomous vehicles and infrastructure networks, e.g., fifth generation (5G) cellular networks. Hence, reliability and latency must be jointly investigated in 5G autonomous vehicular networks. Utilizing the Euclidean norm theory, we first propose a reliability and latency joint function to evaluate the joint impact of reliability and latency in 5G autonomous vehicular networks. The interactions between reliability and latency are illustrated via Monto-Carlo (MC) simulations of 5G autonomous vehicular networks. To improve both the reliability and latency performance and implement URLLC, a new network slicing solution that extends from resource slicing to service and function slicing is presented for 5G autonomous vehicular networks. The simulation results indicate that the proposed network slicing solution can improve both the reliability and latency performance and ensure URLLC in 5G autonomous vehicular networks.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Mar 2019.
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Citing papers per year: 2024: 2; 2025: 1.
3 papers.
- 2024Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networkscited by 6
- 2024PLM-Net: Perception Latency Mitigation Network for Vision-Based Lateral Control of Autonomous Vehiclescited by 3
- 2025Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defensescited by 1
- 2025Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defenses6 Feb 2025
- 2024Model Partition and Resource Allocation for Split Learning in Vehicular Edge Networks11 Nov 2024
- 2024PLM-Net: Perception Latency Mitigation Network for Vision-Based Lateral Control of Autonomous Vehicles23 Jul 2024