Wireless innovations Next-generation
Online Workshop (WiNOW)
3-7 November, 2025 // Virtual
Arumugam Nallanathan
Queen Mary University of London
Arumugam Nallanathan (Fellow, IEEE) is Professor of Wireless Communications and the founding head of the Communication Systems Research (CSR) group in the School of Electronic Engineering and Computer Science at Queen Mary University of London since September 2017. He was with the Department of Informatics at King’s College London from December 2007 to August 2017, where he was Professor of Wireless Communications from April 2013 to August 2017. He was an Assistant Professor in the Department of Electrical and Computer Engineering, National University of Singapore from August 2000 to December 2007. His research interests include 6G Wireless Networks and Internet of Things (IoT). He published nearly 900 technical papers in scientific journals and international conferences. He is a co-recipient of the Best Paper Awards presented at the IEEE International Conference on Communications 2016 (ICC’2016), IEEE Global Communications Conference 2017 (GLOBECOM’2017) and IEEE Vehicular Technology Conference 2017 (VTC’2017). He is a co-recipient of IEEE Communications Society Leonard G. Abraham Prize, 2022.
He was an Editor-at-Large for IEEE Transactions on Communications and a senior editor for IEEE Wireless Communications Letters. He was an Editor for IEEE Transactions on Wireless Communications (2006-2011), IEEE Transactions on Vehicular Technology (2006-2017), IEEE Signal Processing Letters and a Guest Editor for IEEE Journal on Selected Areas in Communications (JSAC). He served as the Chair for the Signal Processing and Computing for Communications (SPCC-TC) of IEEE Communications Society and Technical Program Chair and member of Technical Program Committees in numerous IEEE conferences. He received the IEEE Communications Society SPCE outstanding service award 2012 and IEEE Communications Society RCC outstanding service award 2014. He has been selected as a Web of Science (ISI) Highly Cited Researcher in 2016, 2022-2025. He is an IEEE Fellow and IEEE Distinguished Lecturer.
Talk Title: 6G Meets Large AI Models: Future of Mobile Intelligence
This work studies on ISAC systems for Mobile IoT, emphasizing distributed multi-point architectures that combine active and passive sensing. We first develop a power optimization framework for dual-function radar-communication systems, demonstrating that unlimited backhaul capacity with centralized signal fusion achieves higher target detection probability compared to limited backhaul relying on binary result fusion. Then we introduce a beamforming optimization strategy, distinguishing between the cases with and without sensing interference cancellation. It proves that dedicated sensing signals and optimal beam alignment significantly enhance sensing performance when interference is mitigated. We further propose a deep learning-based auto-compression framework using model-agnostic meta-learning (MAML) to address backhaul constraints. This approach efficiently compresses sensing signals, reducing overhead while maintaining detection accuracy, thus bridging ideal and limited backhaul scenarios. In summary, this work studies power and beamforming optimization issues in distributed multi-point ISAC architectures considering practical backhaul constraints, advancing spectral efficiency and sensing robustness for next-generation mobile IoT.