Analytical Investigation of Two Benchmark Resource Allocation Algorithms for LTE-V2V

TL;DR

This paper analyzes two benchmark resource allocation algorithms for LTE-V2V in highway scenarios, evaluating their performance in terms of packet reception probability using both simplified and realistic traffic models.

Contribution

It identifies two reference algorithms for LTE-V2V resource allocation and evaluates their performance, providing insights into potential improvements.

Findings

PRP varies significantly with different algorithms

Realistic traffic traces show room for performance enhancement

Simplified models help understand algorithm behavior

Abstract

Short-range wireless technologies will enable vehicles to communicate and coordinate their actions, thus improving people's safety and traffic efficiency. Whereas IEEE 802.11p (and related standards) had been the only practical solution for years, in 2016 a new option was introduced with Release 14 of long term evolution (LTE), which includes new features to enable direct vehicle-to-vehicle (V2V) communications. LTE-V2V promises a more efficient use of the channel compared to IEEE 802.11p thanks to an improved PHY layer and the use of orthogonal resources at the MAC layer. In LTE-V2V, a key role is played by the resource allocation algorithm and increasing efforts are being made to design new solutions to optimize the spatial reuse.In this context, an important aspect still little studied, is therefore that of identifying references that allow: 1) to have a perception of the space in which the resource allocation algorithms move; and 2) to verify the performance of new proposals. In this work, we focus on a highway scenario and identify two algorithms to be used as a minimum and maximum reference in terms of the packet reception probability (PRP). The PRP is derived as a function of various parameters that describe the scenario and settings, from the application to the physical layer. Results, obtained both in a simplified Poisson point process scenario and with realistic traffic traces, show that the PRP varies considerably with different algorithms and that there is room for the improvement of current solutions.