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.

根据世界卫生组织的估计，由于道路交通崩溃，每年有超过130万人死亡。自动化最终可以提供更安全的道路和更少的死亡，但是为了使无人驾驶技术成为主流，需要改变很多需要。更有效的沟通和网络对于完全自主驾驶至关重要。建立高级智能运输系统的互联自动驾驶汽车，由于其在提供极大改善的安全性，前所未有的旅行体验并显着提高了交通效率方面的潜力，因此正在受到越来越多的研究关注。这种愿景的核心是无处不在且高度可扩展的车辆到所有通信网络，在该通信网络中，每辆车都可以自由而无缝地“交谈和聆听”其他车辆，人员和机器。这样的V2X通信网络对于启用各种车辆用例的关键是关键。例如，远程驾驶，协调的驾驶和路线计划，车内视频会议/游戏，高分辨率地图下载。通过与一名控制多个车辆的驾驶员的近距离合作构造，称为“排成一座”，对驾驶员的需求将减少，从而解决英国卡车驾驶员短缺。但是，在5G和Be-Beyond移动网络的演变下出现的苛刻车辆渠道，车辆网络的不同性质以及越来越严格的服务质量要求，呼吁增强信号设计和处理算法以适应一个大量用例和通信设备。该项目将开发此类技术，为下一代V2X通信系统奠定基础，以提供更安全，更快，绿色和智能的数据服务。将通过分析和开发更有效，更可靠的车辆传输信号以及它们相应接收器的设计在传输效率，通信时间滞后，接收复杂性和健壮性方面进行了灵活的权衡。通过应用最新的算法来改善传输信号的内在结构特性，并能够全面利用接收器的通道变化，可以预期取得重大进展。通过执行以实用性为导向的研究方法，我们将分析和评估行业首选的车辆频道模型中各种硬件缺陷和实用计算/存储约束的综合效果。鉴于不断增长的密度连接的车辆，我们还将确定高机动性渠道中大规模，可靠和快速车辆通信的有效解决方案。具体而言，通过与AccerlerComm和Viavi解决方案（两家5G通信公司）以及Conigital（自动驾驶汽车开发人员）合作，我们旨在采用系统的设计指南，可行的信号处理算法以及具体的实施方法，以实现可以影响学术界和学术界和学术界和学术界和学术界和学术界和学术界的重要突破性方法行业。此外，通过与挪威的卑尔根大学合作，我们的项目可以通过在补充我们工作的领域中通过增强的数学问题来使更广泛的研究社区受益。总体而言，拟议的项目通过解决以车辆中心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。这些将使高级应用程序所需的改进，以实现未来运输系统的连接自动驾驶汽车愿望。