LLP-V2X: Low Latency-Power Vehicular Networking Towards 6G V2X

2025-11-12

AI Summary

In 6G vehicular networks, achieving both ultra-reliable low-latency communication (URLLC) and high energy efficiency remains challenging due to inherent trade-offs. Method: This paper proposes a Multi-Hop Multi-Path (MHMP) joint optimization framework that jointly models traffic splitting and link-level transmit power allocation, enabling dynamic end-to-end latency–energy trade-offs under strict QoS constraints. A dual-mode adaptive scheduling mechanism is designed to switch on-demand between minimum-latency and minimum-power modes, systematically characterizing the fundamental energy–latency trade-off in 6G V2X. The problem is formulated as a mixed-integer nonlinear program (MINLP), integrating multi-path transmission and dynamic power control. Contribution/Results: Simulation results show that the proposed LLP-MHMP scheduler reduces average end-to-end latency by 32.7% and total energy consumption by 28.4% compared to baseline methods, significantly enhancing the co-optimization of communication reliability and energy efficiency.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Efficient ML / Green AI

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

The trade-off between energy and latency budgets is becoming significant due to the more stringent QoS requirements in 6G vehicular networks. However, comprehensively studying the trade-off between energy and latency budgets for 6G vehicular network with new Vehicle-to-Everything (V2X) features is still under-explored. This paper proposes a novel multi-hop, multi-path vehicular networking that jointly optimizes vehicular traffic splitting across candidate routes and per-link transmit power to achieve low-latency and low-power communications. Afterwards, we formalize two complementary problem formulations (minimum latency and minimum power) based on the proposed 6G V2X architecture and provide sufficient conditions. The performance of the proposed scheme is evaluated via well-designed simulations. Based on these theories, we design algorithm (LLP MHMP Scheduler) that switches on demand between a fixed-power minimum-latency mode and a fixed-latency minimum-power mode.

Problem

• Optimizing energy-latency tradeoff in 6G vehicular networks
• Developing multi-hop multi-path V2X communication scheduling
• Achieving low-latency low-power transmissions through joint optimization

Innovation

• Multi-hop multi-path vehicular networking optimization
• Joint traffic splitting and transmit power optimization
• Algorithm switches between latency and power modes