IEEE Windsor Section

IEEE

AI in 6G Networks – Path From Enabler to AI Native Air Interface

The upcoming event “AI in 6G Networks – Path From Enabler to AI Native Air Interface” will be held on Friday, 10 November 2022, co-hosted by IEEE Windsor Section Joint Chapter SP01/COM19.

For registration and more information, please visit:

https://events.vtools.ieee.org/m/329644

Abstract: 

Machine learning (ML) and AI will play a key role in the development of 6G networks. Network virtualization and network softwarization solutions in 5G networks can support data-driven intelligent and automated networks to some extent and this trend will grow in 5G-advanced networks. Radio access network algorithms and radio resource management functions can exploit network intelligence to fine tune network parameters to reach close-to-optimal performance in 5G networks. In 6G networks, network intelligence is envisioned to be end-to-end, and air interface is envisioned to be AI-native. The user equipment (UE) devices need to be smarter, environment and context aware, and capable of running ML algorithms. This talk will focus on the main practical challenges in developing machine learning solutions in 5G use cases and emphasize with a case study how deployment of these solutions is much harder in a live network as compared to theoretical performance evaluation. Further, a vision for paradigm shift from AI-as-an-enabler to AI-Native air-interface will be provided for 6G networks.

Speaker: Dr. Majid of Nokia Bell Labs

Biography:

M. Majid Butt received the M.Sc. degree in digital communications from Christian Albrechts University, Kiel, Germany, in 2005, and the Ph.D. degree in telecommunications from the Norwegian University of Science and Technology, Trondheim, Norway, in 2011. He is a senior research specialist at Nokia Bell Labs, France, and an adjunct Research Professor at Trinity College Dublin, Dublin, Ireland. Prior to that, he has held various positions at the University of Glasgow, U.K., Trinity College Dublin, Ireland, and Fraunhofer HHI, Germany. His current research interests include communication techniques for wireless networks with a focus on radio resource allocation, scheduling algorithms, energy efficiency, and machine learning for RAN. He has authored more than 75 peer-reviewed conference and journal articles, 4 book chapters and filed over 30 patents in these areas. He frequently gives invited and technical tutorial talks on various topics in IEEE conferences including, ICC, Globecom, VTC, etc.

Dr. Butt was a recipient of the Marie Curie Alain Bensoussan Post-Doctoral Fellowship from the European Research Consortium for Informatics and Mathematics. He has organized several technical workshops on various aspects of communication systems in conjunction with major IEEE conferences. He serves as an associate editor for IEEE Communication Magazine, IEEE Open Journal of the Communication Society and IEEE Open Journal of Vehicular Technology.