Situational Coverage and Rate Distribution Maps for 5G V2X Systems Using Ray-Tracing

TL;DR

This paper develops situational rate maps for 5G V2X mmWave systems using ray-tracing, analyzing how physical and system parameters affect coverage and rate distribution for autonomous vehicle communication.

Contribution

It introduces a novel method to generate rate distribution maps for 5G V2X using ray-tracing, considering various physical architectures and deployment scenarios.

Findings

Rate maps vary significantly with carrier frequency and bandwidth.

Physical architecture impacts the coverage and rate distribution.

Blockages and deployment strategies influence the communication performance.

Abstract

Millimeter wave (mmWave) is a practical solution to provide high data rate for vehicle-to-everything (V2X) communications. This enables the future autonomous vehicles to exchange big data with the base stations (BSs) such as the velocity, and the location to enhance the safety for the advanced driving assistance system (ADAS). To achieve this goal, we propose to develop a situational rate map to characterize the distribution of the rates achieved between the BSs and a uniform grid of vehicles. In this context, we consider a mmWave 5G cellular system with two physical structures which are the analog-only beamforming and hybrid precoding with limited feedback to investigate the rate distribution for single and multiuser scenarios. We will use the Ray-Tracing tool to construct the simulation environment and generate the channels between the BSs and the grid of vehicles. Finally, we will study the effects of the carrier frequency, the bandwidth, the BSs deployment, the blockage, the codebook, the physical architectures and the number of served users on the rate distribution maps. Moreover, we will present the rate statistics to evaluate the coverage of served users for certain services requirements and for various road shapes such as corners, intersections and straightways.