Latency Analysis of 5G C-V2X Real-Time Video Transmission Over Different Channel States

Abstract

For future applications such as sensor sharing, computation task offloading for autonomous driving, and remote driving, robust real-time video transmission with low latency via cellular vehicle-to-everything (C-V2X) communication is essential to ensure operational reliability. While advanced communication services require sensor sharing, yet there is a lack of comprehensive latency analysis for high-volume data between vehicles and remote users or servers. Existing literature predominantly focuses on vehicle-to-vehicle communication or basic device status messages with low volume, which are insufficient for supporting advanced services such as autonomous driving. Consequently, it is crucial to analyze the latency involved in sensor sharing between vehicle and remote entity over different channel states. In this paper, the latency of sensor data transmission using 5G C-V2X Uu interface is investigated in consideration of various channel states and modulation and coding schemes. Additionally, we analyzed the latency depending on the resolution and encoding of the camera video image. Simulation results show the feasible frame rates and video resolutions for both raw and compressed video transmissions within these communication systems, and highlight the effects of channel state and multi-user scenarios on the feasibility of real-time camera video sharing.