Ultra-Reliable and Low-Latency for Vehicle-to-Everything (V2X) Communications

This project proposal aims to explore ultra-reliable and low-latency communications (URLLC) in vehicle-to-everything (V2X) communications. V2X is a key technology in Intelligent Transportation System (ITS), enabling wireless communication between vehicles and its environments such as other vehicles, infrastructure, pedestrians, and networks.
Intelligent Transportation System provides users an improved journey experience by employing vehicle sensors, information exchange and communication between enabled V2X elements. It is essential to implement ultra-reliable and low-latency V2X in Intelligent Transportation System because it provides a vital component in vehicle safety such as collision avoidance, autonomous driving, and intelligent motorways.

However, V2X communication faces unique challenges due to characteristics involving quick changing environments, high mobility, and relatively low antenna heights. These characteristics provide difficulties in implementing low end-to-end latency and high reliability for V2X communications. For example, the propagation channel changes frequently due to the fast changing environment. This means the channel needs to be estimated frequently which require complex computation.

The improvement of V2X latency and reliability has imposed new challenges to the management of radio resource and network resource. Currently, the network enhancement that is being under research and development is multi-access edge computing (MEC), formerly mobile edge computing. MEC uses cloud technology at the radio access network (RAN) edge which is near the end users. By using MEC, data will be processed at the local edge using traffic offloading which could decrease the traffic load of the mobile backhaul and the core network. There are several MEC-enabled applications for V2X such as platooning, collaborative networking and vulnerable road user safety. This is implemented by providing instructions to users by collecting data from multiple nearby vehicles and networks. The data will be processed at the cloud edge using powerful computers. Therefore, MEC is a promising method and could provide ultra-low latency to the development of V2X. However, there are challenges in MEC-enabled V2X to be solved.

These challenges include, firstly, the existing V2X communications systems such as cellular-V2X, mmWave and IEEE 802.11p, which does not satisfy the requirements for URLLC but is necessary for many of the MEC-enabled applications. Secondly, the future deployment of a large number of small 5G cells are needed to provide continuous coverage but high-speed vehicles in V2X would require frequent handover procedures. As such, it is essential for several MEC-enabled applications to maintain continuity during handover. Lastly, 5G networks are heterogenous which is an advantage as different communication technologies and existing infrastructure can be amalgamated into the 5G network. However, as MEC deploys its resources at the RAN edge and near end users, with different communication technologies and this would require a very complex resource management. In addition, the heterogeneous nature of 5G networks would further complicate the application of Cooperative Awareness Messages (CAMs) in every vehicle which provides basic information such as location, destination, and speed.

In this project, the solution to the challenges of implementing MEC-enabled application in V2X will be investigated. The potential tasks are creating a new channel model for the V2X environment and identifying key parameters that affect the reliability and latency of the signals, as well as the proposition and design of a new method for resource management at the cloud edge. Lastly, the addition of new applications, other than MEC to be used in V2X communications will be explored.