# 5G NR-V2X: Towards Connected and Cooperative Autonomous Driving

arXiv: https://arxiv.org/abs/2009.03638 · HTML: https://mlsanity.com/paper/2009.03638/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Sep 2020.

## Built on by (most cited first, 3 of 3)

- [A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services](https://mlsanity.com/paper/2304.14271/) (2023)
- [Event-Triggered Reinforcement Learning Based Joint Resource Allocation for Ultra-Reliable Low-Latency V2X Communications](https://mlsanity.com/paper/2407.13947/) (2024)
- [Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection](https://mlsanity.com/paper/2405.17497/) (2024)

## Abstract (arXiv)

This paper is concerned with the key features and fundamental technology components for 5G New Radio (NR) for genuine realization of connected and cooperative autonomous driving. We discuss the major functionalities of physical layer, Sidelink features and its resource allocation, architecture flexibility, security and privacy mechanisms, and precise positioning techniques with an evolution path from existing cellular vehicle-to-everything (V2X) technology towards NR-V2X. Moreover, we envisage and highlight the potential of machine learning for further enhancement of various NR-V2X services. Lastly, we show how 5G NR can be configured to support advanced V2X use cases in autonomous driving.