AI-Native Resource Management for 6G: From Deep Unsupervised Learning to Generative Intelligence

Abstract: The unprecedented scale, heterogeneity, and performance requirements of 6G networks fundamentally challenge traditional optimization-centric approaches to resource management, motivating a paradigm shift toward artificial intelligence (AI)–driven methodologies. This lecture examines how deep unsupervised learning and generative AI techniques can be leveraged to solve both convex and non-convex network resource allocation problems under complex, nonlinear constraints. Particular emphasis is placed on deep unsupervised learning frameworks, deep implicit layers, and differentiable projection methods that enforce strict constraint satisfaction in applications such as beamforming, phase-shift optimization, and power allocation. The emerging role of generative AI models, including large language models (LLMs), is further discussed in enabling adaptive and environment-aware resource allocation strategies that reduce dependence on frequent model redesign and retraining. The lecture concludes by identifying key research challenges and outlining a roadmap toward scalable, robust, and AI-native 6G wireless <a href="http://networks.

Speaker” target=”_blank” title=”networks.

Speaker”>networks.

Speaker Bio: Hina Tabassum (Senior Member, IEEE) received the Ph.D. degree from the King Abdullah University of Science and Technology. She is currently an Associate Professor with the Lassonde School of Engineering, York University, Canada, where she joined as an Assistant Professor in 2018. She is also appointed as a Visiting Faculty with the University of Toronto in 2024, and the York Research Chair of 5G/6G-enabled mobility and sensing applications in 2023, for five years. She is listed in Stanford’s list of the World’s Top Two-Percent Researchers from 2021 to 2025. She has been selected as the IEEE ComSoc Distinguished Lecturer for the term 2025–2026. She has co-authored over 120 refereed articles in well-reputed IEEE journals, magazines, and conferences. Her current research interests include multiband 6G wireless communications and sensing networks, connected and autonomous systems, and AI-enabled network mobility and resource management solutions. She has earned numerous distinctions, including the N2Women Star in Networking and Communications (2025), Early Career Lassonde Innovation Award (2023), N2Women Rising Star in Networking and Communications (2022), multiple Exemplary Editor awards from IEEE journals, and appointment to the NSERC Discovery Grant Evaluation Group (2025–2028). She served as an Associate Editor for IEEE Communications Letters from 2019 to 2023, IEEE Open Journal of the Communications Society from 2019 to 2023, and IEEE Transactions on Green Communications and Networking from 2020 to 2023. She is also currently serving as an Area Editor for IEEE Open Journal of the Communications Society and an Associate Editor for IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, IEEE Transactions on Wireless Communications, and IEEE Communications Surveys and <a href="http://Tutorials.

Bldg:” target=”_blank” title=”Tutorials.

Bldg:”>Tutorials.

Bldg: ICT 424C, University of Calgary, Calgary, Alberta, Canada