6G for Vehicle-to-Everything (V2X) Communications: Enabling Technologies, Challenges, and Opportunities

TL;DR

This paper discusses the potential of 6G technology to revolutionize vehicle-to-everything communications by enabling ultra-reliable, low-latency, and intelligent vehicular networks through advanced materials, algorithms, and machine learning integration.

Contribution

It provides a comprehensive overview of key enabling technologies for 6G V2X, highlighting recent advances, challenges, and future research directions, especially in machine learning applications.

Findings

Identification of new materials and system architectures for 6G V2X

Analysis of machine learning's role in intelligent vehicular networks

Discussion of open challenges and future research opportunities

Abstract

We are on the cusp of a new era of connected autonomous vehicles with unprecedented user experiences, tremendously improved road safety and air quality, highly diverse transportation environments and use cases, as well as a plethora of advanced applications. Realizing this grand vision requires a significantly enhanced vehicle-to-everything (V2X) communication network which should be extremely intelligent and capable of concurrently supporting hyper-fast, ultra-reliable, and low-latency massive information exchange. It is anticipated that the sixth-generation (6G) communication systems will fulfill these requirements of the next-generation V2X. In this article, we outline a series of key enabling technologies from a range of domains, such as new materials, algorithms, and system architectures. Aiming for truly intelligent transportation systems, we envision that machine learning will play an instrumental role for advanced vehicular communication and networking. To this end, we provide an overview on the recent advances of machine learning in 6G vehicular networks. To stimulate future research in this area, we discuss the strength, open challenges, maturity, and enhancing areas of these technologies.