Project description
6G Space-Air-Ground-Sea Integrated Networks (SAGSIN) are envisioned to connect satellite, aerial, ground, and sea networks to provide connectivity everywhere and all the time. However, how to coordinate these networks and manage heterogeneous resources to satisfy the requirements of different applications remains to be solved. In this project, we investigate the resource management-based link scheduling in SAGSIN for marine applications. The major enabler for these applications is the provision of low-delay, and reliable wireless coverage to the ever-increasing number of underwater sensors. In fact, once marine data are generated by underwater sensors, it can be scheduled to access an appropriate network of SAGSIN and an appropriate node on that network while respecting the link lifetime, energy efficiency and latency to ensure efficient delivery to the onshore station. Indeed, forwarding this data in a multihop scheme to reach first the surface ships or buoys won’t be enough to ensure delivery to the onshore station. Thus, a possible data transfer to specially launched UAVs with a preplanned trajectory may facilitate delivery to the final destination. Given that UAVs are energy constrained, offloading the data to satellites that can reach the onshore station wherever deployed either directly or through terrestrial IoT networks is an attractive solution. Given the mobility and resource constraint of the underwater sensors, UAVs, and satellites, along with their sensitivity to environmental conditions, deriving the optimal link to be used at each layer at every time is a challenging large scale scheduling problem.
The successful candidate will work closely with expert researchers and contribute to high-impact publications. This studentship is an exciting opportunity to develop innovative AI solutions that will enhance coverage of hard-to-reach areas, real time data delivery, and UAVs trajectory planning, shaping the future of 6G SAGSIN communication.