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

超可靠、低延迟的车联网 (V2X) 通信

• 批准号: 2619790
• 金额: --
• 依托单位: University of Kent
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2619790
• 关键词: Ultra; Reliable; Low; Latency; Vehicle

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.

该项目提案旨在探索车对万物（V2X）通信中的超可靠和低延迟通信（URLLC）。 V2X 是智能交通系统 (ITS) 的一项关键技术，可实现车辆与其环境（例如其他车辆、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、信息交换以及启用的 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，因为它为防撞、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，由于环境快速变化、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。这些特性为实现V2X通信的低端到端延迟和高可靠性带来了困难。例如，由于环境的快速变化，传播信道频繁变化。这意味着需要频繁地估计信道，需要复杂的计算。V2X时延和可靠性的提高给无线资源和网络资源的管理带来了新的挑战。目前，正在研究和开发的网络增强是多接入边缘计算（MEC），以前称为移动边缘计算。 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，这可以减少移动回程和核心网络的流量负载。有多种支持 MEC 的 V2X 应用程序，例如队列行驶、协作网络和脆弱道路用户安全。这是通过从附近的多个车辆和网络收集数据来向用户提供指令来实现的。数据将使用功能强大的计算机在云端进行处理。因此，MEC是一种很有前景的方法，可以为V2X的开发提供超低延迟。然而，支持MEC的V2X还存在一些挑战需要解决。这些挑战首先包括现有的V2X通信系统，例如蜂窝V2X、毫米波和IEEE 802.11p，这些系统不能满足URLLC的要求，但对于许多支持MEC的应用来说是必需的。其次，未来需要部署大量小型5G小区来提供连续覆盖，但V2X中的高速车辆需要频繁的切换程序。因此，对于多个支持 MEC 的应用程序来说，在切换期间保持连续性至关重要。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 边缘和近端用户，采用不同的通信技术，这将需要非常复杂的资源管理。此外，5G 网络的异构性将使每辆车中提供位置、目的地和速度等基本信息的协作感知消息 (CAM) 的应用进一步复杂化。 在该项目中，将研究在 V2X 中实施 MEC 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，识别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，除了用于 V2X 通信的 MEC 之外，还将探索添加新的应用程序。