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

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.