Intelligent and Proactive Optimisation for Service-centric Wireless Networks

MSCA (Marie Skłodowska-Curie)HORIZON-TMA-MSCA-SEID: 101086219
EC Contribution
€3,726
Consortium Size
6 orgs
Start Year
2023
Summary

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.

Consortium (6)

Project Results (12)

Source: CORDIS, the EU research results database.

Publications (5)
Deployment Strategy of Intelligent Omni-Surface-Assisted Outdoor-to-Indoor Millimeter-Wave Communications
IEEE Transactions on Wireless Communications· 2025DOI
Zhiyu Liu, Xiaoli Chu, David López-Pérez, Na Tang
On the Performance of an Integrated Communication and Localization System: An Analytical Framework
IEEE Transactions on Vehicular Technology· 2024DOI
Yuan Gao; Haonan Hu; Jiliang Zhang; Yanliang Jin; Shugong Xu; Xiaoli Chu
Online Learning for Intelligent Thermal Management of Interference-Coupled and Passively Cooled Base Stations
IEEE Transactions on Machine Learning in Communications and Networking· 2024DOI
Zhanwei Yu, Yi Zhao, Xiaoli Chu, Di Yuan
Learn to Stay Cool: Online Load Management for Passively Cooled Base Stations
Proceedings of IEEE Wireless Communications and Networking Conference (WCNC)DOI
Z. Yu, Y. Zhao, L. You, and D. Yuan
Less Carbon Footprint in Edge Computing by Joint Task Offloading and Energy Sharing
IEEE Networking LettersDOI
Z. Yu, Y. Zhao, T. Deng, L. You, and D. Yuan
Deliverables (7)