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

该项目提案旨在探索车联网（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，可实现车辆与其环境（如其他车辆、基础设施、行人和网络）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V2X元素之间的通信，为用户提供更好的旅程体验。在智能交通系统中实现超可靠和低延迟的V2X至关重要，因为它为避免碰撞、自动驾驶和智能高速公路等车辆安全提供了重要组成部分。然而，由于快速变化的环境、高移动性和相对较低的天线高度等特点，V2X通信面临着独特的挑战。这些特点为实现低端到端延迟和高可靠性的V2X通信提供了困难。例如，由于环境的快速变化，传播通道频繁变化。这意味着需要频繁地估计信道，这需要复杂的计算。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接入边缘计算（MEC），前身是移动边缘计算。MEC在靠近最终用户的无线接入网（RAN）边缘使用云技术。通过MEC，数据将在本地边缘进行处理，使用流量分流，可以减少移动回程和核心网的流量负载。V2X有几种支持mec的应用，如队列行驶、协作网络和脆弱的道路使用者安全。这是通过收集附近多个车辆和网络的数据向用户提供指令来实现的。数据将在云边缘使用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的发展提供超低延迟。然而，在支持mec的V2X中存在一些挑战需要解决。这些挑战包括，首先，现有的V2X通信系统，如蜂窝V2X、毫米波和IEEE 802.11p，不满足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中的高速车辆需要频繁的交接程序。因此，对于几个支持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网络是异构的，这是一个优势，因为不同的通信技术和现有的基础设施可以合并到5G网络中。然而，由于MEC将其资源部署在RAN边缘和终端用户附近，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网络的异构特性将进一步复杂化协同感知信息（CAMs）在每辆车中的应用，CAMs提供诸如位置、目的地和速度等基本信息。在该项目中，将研究在V2X中实现支持mec的应用所面临的挑战的解决方案。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用于云边缘资源管理的新方法。最后，将探索除MEC之外用于V2X通信的新应用。

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.