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

本项目提案旨在探索车辆到一切(V2X)通信中的超可靠和低延迟通信(URLLC)。V2X是智能交通系统(ITS)中的一项关键技术，它实现了车辆与其他车辆、基础设施、行人和网络等环境之间的无线通信。智能交通系统通过使用车辆传感器、信息交换和启用的V2X元素之间的通信，为用户提供了更好的出行体验。在智能交通系统中实现超可靠、低延迟的V2X是至关重要的，因为它是车辆安全的重要组成部分，如防撞、自动驾驶和智能高速公路。然而，由于V2X通信环境变化快、移动性高、天线高度相对较低等特点，V2X通信面临着独特的挑战。这些特性给实现V2X通信的低端到端延迟和高可靠性带来了困难。例如，传播信道由于快速变化的环境而频繁变化。这意味着需要频繁地估计信道，计算复杂，V2X时延和可靠性的提高对无线资源和网络资源的管理提出了新的挑战。目前，正在研究和开发的网络增强是多路访问边缘计算(MEC)，即以前的移动边缘计算。MEC在靠近最终用户的无线接入网络(RAN)边缘使用云技术。通过使用MEC，数据将在本地边缘使用流量卸载进行处理，从而降低移动回程和核心网的流量负载。V2X有几个支持MEC的应用程序，如排队、协作网络和易受攻击的道路用户安全。这是通过从附近的多个车辆和网络收集数据向用户提供指令来实现的。这些数据将在云端使用功能强大的计算机进行处理。因此，MEC是一种很有前途的方法，可以为V2X的开发提供超低延迟。然而，在支持MEC的V2X中也存在需要解决的挑战，这些挑战包括：第一，现有的V2X通信系统，如蜂窝V2X、毫米波和IEEE 802.11p，它们不能满足URLLC的要求，但对于许多支持MEC的应用来说是必要的。其次，未来需要部署大量小型5G小区来提供持续覆盖，但V2X中的高速车辆将需要频繁的切换程序。因此，对于几个启用MEC的应用程序来说，在切换期间保持连续性是至关重要的。最后，5G网络是异构性的，这是一个优势，因为不同的通信技术和现有基础设施可以融合到5G网络中。然而，由于MEC将其资源部署在RAN边缘和近端用户，使用不同的通信技术，这将需要非常复杂的资源管理。此外，5G网络的异构性将使协同感知消息(CAM)在每辆车中的应用进一步复杂化，该消息提供位置、目的地和速度等基本信息。在本项目中，将研究在V2X中实现MEC支持的应用的挑战的解决方案。潜在的任务是为V2X环境创建新的通道模型，确定影响信号可靠性和延迟的关键参数，以及提出和设计一种新的云边缘资源管理方法。最后，将探讨在V2X通信中使用的除MEC之外的其他新应用。

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.