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.

该项目的建议旨在探索在车辆到所有通信中的超级可靠和低延迟通信（URLLC）。 V2X是智能运输系统（ITS）的关键技术，可以在车辆及其环境之间进行无线通信，例如其他车辆，基础设施，行人和网络。IntelligentTransportation System通过采用车辆传感器，信息交换和启用V2X元素之间的交换，为用户提供改进的旅程体验。在智能运输系统中实施超级可靠和低延迟的V2X是至关重要的，因为它为车辆安全性提供了重要组成部分，例如避免碰撞，自动驾驶和智能高速公路。这些特征在实施低端到端延迟和对V2X通信的高可靠性方面遇到了困难。例如，由于环境快速变化，传播渠道经常发生变化。这意味着需要频繁估算频道，这需要复杂的计算。V2X延迟和可靠性的改善为无线电资源和网络资源的管理带来了新的挑战。当前，正在研究和开发的网络增强是多访问边缘计算（MEC），以前是移动边缘计算。 MEC在最终用户附近的无线电访问网络（RAN）边缘使用云技术。通过使用MEC，将使用流量卸载在本地边缘处理数据，这可能会减少移动回程和核心网络的流量负载。有几个针对V2X的MEC应用程序，例如排量，协作网络和脆弱的道路用户安全。通过从多个附近的车辆和网络收集数据向用户提供指令来实现这一点。数据将使用强大的计算机在云边缘处理。因此，MEC是一种有前途的方法，可以为V2X的发展提供超低潜伏期。但是，要解决的启用MEC的V2X面临挑战。这些挑战首先包括现有的V2X通信系统，例如Cellular-V2X，MMWave和IEEE 802.11p，这些系统不满足URLLC的要求，但对于许多MEC启用了MEC的应用程序都是必需的。其次，需要大量小5G单元的未来部署以提供连续的覆盖范围，但是V2X中的高速车辆将需要经常进行切换程序。因此，几个支持MEC的应用程序在移交过程中保持连续性至关重要。最后，5G网络是异质的，这是一个优势，因为可以将不同的通信技术和现有基础架构合并到5G网络中。但是，随着MEC通过不同的通信技术部署其资源在Edge和近最终用户中，这将需要非常复杂的资源管理。此外，5G网络的异质性质将使合作意识消息（CAM）在提供基本信息（例如位置，目的地和速度）的每辆车中的应用更加复杂。潜在的任务是为V2X环境创建新的频道模型，并确定影响信号可靠性和延迟的关键参数，以及在云边缘的新方法的命题和设计。最后，将探索除了在V2X通信中使用的MEC以外的新应用程序的添加。