# Towards Low-Latency and Ultra-Reliable Vehicle-to-Vehicle Communication

## TL;DR

This paper introduces a proximity and QoS-aware resource allocation scheme for V2V communication that significantly reduces latency and improves reliability by leveraging spatial-temporal vehicle data and a novel clustering approach.

## Contribution

It proposes a new RSU-assisted clustering and resource allocation method that minimizes power while meeting latency and reliability requirements in V2V networks.

## Key findings

- Latency reduced by up to 97% in simulations.
- Significant reliability improvements observed.
- Effective clustering based on vehicle proximity enhances resource efficiency.

## Abstract

Recently vehicle-to-vehicle (V2V) communication emerged as a key enabling technology to ensure traffic safety and other mission-critical applications. In this paper, a novel proximity and quality-of-service (QoS)-aware resource allocation for V2V communication is proposed. The proposed approach exploits the spatial-temporal aspects of vehicles in terms of their physical proximity and traffic demands, to minimize the total transmission power while considering queuing latency and reliability. Due to the overhead caused by frequent information exchange between vehicles and the roadside unit (RSU), the centralized problem is decoupled into two interrelated subproblems. First, a novel RSU-assisted virtual clustering mechanism is proposed to group vehicles in zones based on their physical proximity. Given the vehicles' traffic demands and their QoS requirements, resource blocks are assigned to each zone. Second, leveraging techniques from Lyapunov stochastic optimization, a power minimization solution is proposed for each V2V pair within each zone. Simulation results for a Manhattan model have shown that the proposed scheme outperforms the baseline in terms of average queuing latency reduction up to 97% and significant improvement in reliability.