New Signal Design and Processing for Future Vehicular Communications (DRIVE)

未来车辆通信 (DRIVE) 的新信号设计和处理

• 批准号: EP/X035352/1
• 负责人: Zilong Liu
• 金额: $ 32.42万
• 依托单位: University of Essex
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX035352%2F1
• 关键词: New; Signal; Design; Processing; Future

Over 1.3 million people die each year because of road traffic crashes, according to the estimate of World Health Organisation. Automation could ultimately provide safer roads and less fatalities, but in order for driverless technology to become mainstream, much needs to change; more efficient communication and networking are essential for fully autonomous driving. Connected autonomous vehicles building upon advanced intelligent transportation systems are receiving increasing research attention due to their potentials in delivering tremendously improved safety, unprecedented travel experiences, and significantly enhanced traffic efficiency. Central to this vision is a ubiquitous and highly scalable vehicle-to-everything (V2X) communication network in which every vehicle can "talk and listen" to other vehicles, people, and machines, freely and seamlessly. Such a V2X communication network is pivotal for the enabling of a rich variety of vehicular use cases. For instance, remote driving, coordinated driving & route planning, in-car video conferencing/gaming, high-resolution map downloading. By enabling travel in close cooperative formations with one driver controlling multiple vehicles, called 'platooning', the need for drivers would reduce thereby addressing the truck driver shortages in the UK. The harsh vehicular channels, the varying nature of vehicular networks, and the increasingly stringent quality-of-service requirements that arise under the evolution of the 5G-and-beyond mobile networks, however, call for enhanced signal design and processing algorithms to accommodate a vast range of use cases and communication devices. This project will develop such technology to lay the foundations for the next generation V2X communication systems to deliver safer, faster, greener, and smarter data services.Innovations will be made by analysing and developing more efficient and reliable vehicular transmission signals as well as their corresponding receiver designs to strike a flexible trade-off in terms of transmission efficiency, communication time lags, reception complexity and robustness. Major advances are expected by our application of the most up-to-date algorithms to improve the intrinsic structural properties of the transmission signals and to enable the full exploitation of the channel variations at the receiver. By carrying out a practicality-oriented research method, we will analyse and evaluate the combined effects of various hardware imperfections and practical computing/storage constraints in the industry preferred vehicular channel models. In view of the ever-growing densely connected vehicles, we will also determine effective solutions for massive, reliable, and rapid vehicular communications in high mobility channels. Specifically, by working with AccerlerComm and VIAVI Solution (two 5G communications companies), and Conigital (an autonomous vehicle developer), we aim for systematic design guidelines, feasible signal processing algorithms, and concrete implementation approaches for significant breakthroughs that can influence both academia and industry. Moreover, by collaborating with the University of Bergen in Norway, our project could for instance benefit the wider research community with enhanced mathematical problem solving in areas which complement our work. Overall, the proposed project seeks ground-breaking research outcomes by addressing several fundamental problems in vehicle-centric transmission signal design and receiver processing. These will enable the improvements required for advanced applications to achieve the connected autonomous vehicle aspirations for future transportation systems.

据世界卫生组织估计，每年有130多万人死于道路交通事故。自动化最终可以提供更安全的道路和更少的死亡率，但为了使无人驾驶技术成为主流，还需要做出很多改变;更有效的通信和网络对于完全自动驾驶至关重要。基于先进智能交通系统的互联自动驾驶汽车正受到越来越多的研究关注，因为它们具有极大提高安全性、前所未有的旅行体验和显著提高交通效率的潜力。这一愿景的核心是一个无处不在、高度可扩展的车联网（V2X）通信网络，在这个网络中，每辆车都可以自由、无缝地与其他车辆、人和机器“交谈和倾听”。这种V2X通信网络对于实现各种各样的车辆用例至关重要。例如，远程驾驶，协调驾驶和路线规划，车载视频会议/游戏，高分辨率地图下载。通过使旅行在密切合作的编队与一个司机控制多辆车，所谓的“排队”，对司机的需求将减少，从而解决卡车司机短缺在英国。然而，在5G及更高移动的网络的演进下出现的苛刻的车辆信道、车辆网络的变化性质以及日益严格的服务质量要求，要求增强的信号设计和处理算法以适应广泛的用例和通信设备。该项目将通过分析和开发更高效、更可靠的车载传输信号及其相应的接收机设计，在传输效率、通信时延、接收复杂度和鲁棒性等方面进行灵活的权衡，从而实现创新，为下一代V2X通信系统提供更安全、更快速、更绿色、更智能的数据服务奠定基础。我们应用最新的算法来改善传输信号的固有结构特性，并使接收机能够充分利用信道变化，预计将取得重大进展。通过开展面向实践的研究方法，我们将分析和评估各种硬件缺陷和实际的计算/存储限制在行业首选的车辆通道模型的综合影响。鉴于日益增长的密集连接车辆，我们还将确定在高流动性通道中实现大规模、可靠和快速车辆通信的有效解决方案。具体来说，通过与AccerlerComm和VIAVI Solution（两家5G通信公司）以及Conigital（一家自动驾驶汽车开发商）合作，我们的目标是系统的设计指南，可行的信号处理算法和具体的实现方法，以实现可以影响学术界和工业界的重大突破。此外，通过与挪威的卑尔根大学合作，我们的项目可以使更广泛的研究界受益，在补充我们工作的领域增强数学问题解决能力。总的来说，拟议的项目通过解决以车辆为中心的传输信号设计和接收器处理中的几个基本问题来寻求突破性的研究成果。这些将使先进应用所需的改进成为可能，以实现未来交通系统的互联自动驾驶汽车愿望。