Artificial Intelligence-enabled Proactive Optimisation for Mobile Communication Networks (EEE-09-Chu)
Details
Wireless networks have become indispensable to citizens, enterprises and vertical industries, e.g. transport (including autonomous vehicles and drones), logistics, utilities and manufacturing, because wireless connectivity is essential to the digital transformation of industrial and business processes and customer experiences.
As a result, wireless networks are facing increasingly diverse service requirements, which indicate that existing reactive network management will be insufficient, while intelligent and proactive control of service-centric networks becomes essential.
Future intelligent wireless networks rely on several multidisciplinary breakthroughs:
(i) Artificial Intelligence (AI) algorithms that can accurately predict spatial-temporal patterns of service demand and thereby drive proactive optimisation of wireless networks, (ii) reconfigurable radio access networks (RAN) and wireless environments, and (iii) automated wireless service provisioning with reduced cost, improved performance and greater reliability.
Current research to automate the optimisation of service-centric wireless networks using data-driven AI is facing many open challenges that need to be urgently addressed. In this project, we will take advantage of growing data availability and advanced data science technologies, as well as AI algorithms and techniques to deliver the above identified multidisciplinary breakthroughs, thereby enabling reliable automated wireless service provisioning. Interested candidates are strongly encouraged to contact the project supervisors to discuss your interest in and suitability for the project prior to submitting your application.
Please refer to the EPSRC DTP webpage for detailed information about the EPSRC DTP and how to apply.
Apply Here: Application Form (sheffield.ac.uk)
Funding Notes
The award will fund the full (UK or Overseas) tuition fee and UKRI stipend (currently £18,622 per annum) for 3.5 years, as well as a research grant to support costs associated with the project.