Keynote speakers
Deniz Gündüz: Generative AI for Wireless Communication
Abstract: Over the past few years, significant advancements have taken place in the field of wireless image/video delivery, thanks to the utilization of deep neural networks (DNNs) for joint source-channel coding. This approach, known as Deep Joint Source-Channel Coding (DeepJSCC), operates in an end-to-end fashion, eliminating the need for separate blocks for compression, channel coding, modulation, and power allocation, and can outperform conventional separation-based approaches. Concurrently, the domain of generative AI has made significant strides, garnering attention for its impressive applications in photorealistic image generation and conversational agents. In this talk, I will showcase how DeepJSCC can be combined with powerful pretrained generative models to enable a notable enhancement in the quality of reconstructed images at the receiver. By leveraging Generative DeepJSCC, which incorporates generative adversarial networks (GANs) or potent diffusion models, it becomes possible to produce realistic images with high fidelity, even under extreme conditions of limited bandwidth and low signal-to-noise ratio. This novel communication paradigm opens up exciting possibilities such as enabling wireless gaming and enriching metaverse experiences.
Biography: Deniz Gündüz is a Professor of Information Processing in the Electrical and Electronic Engineering Department at Imperial College London, UK, where he also serves as the deputy head of the Intelligent Systems and Networks Group. His research interests lie in the areas of communications and information theory, machine learning, and privacy. Dr. Gündüz is a Fellow of the IEEE. He is an elected member of the IEEE Signal Processing Society Signal Processing for Communications and Networking (SPCOM) and Machine Learning for Signal Processing (MLSP) Technical Committees. He is the recipient of the IEEE Communications Society – Communication Theory Technical Committee (CTTC) Early Achievement Award in 2017, Starting (2016) and Consolidator (2022) and Proof-of-Concept (2023) Grants of the European Research Council (ERC), and has co-authored several award-winning papers, most recently the IEEE Communications Society – Young Author Best Paper Award (2022), and the IEEE International Conference on Communications Best Paper Award (2023).
Liesbet Van Der Perre: Remote IoT nodes: in need of a flying doctor?
Biography: Liesbet Van der Perre is Professor at the department of Electrical Engineering at the KU Leuven in Belgium. She received her Ph.D. degree from the KU Leuven in 1997. Dr. Van der Perre was with the nano-electronics research institute imec in Belgium from 1997 till 2015 where she took up responsibilities from system architect to director of the wireless program. Prof. L. Van der Perre’s main research interests are in wireless communication and embedded connected systems, with a current focus on energy efficient solutions for IoT and 6G systems. She has (co-)authored over 400 scientific papers and 4 books. Liesbet Van der Perre has been serving as an advisor and board member for companies, institutes, and funding agencies. She was the scientific coordinator of the European project ‘MAMMOET’ (2014-2017) progressing massive MIMO technology for efficient transmission, and currently takes up this role for the European H2020 REINDEER and Horizon Europe 6GTandem projects.
Luca Sanguinetti: Holographic MIMO Communications: What is the benefit of closely spaced antennas?
Abstract: Holographic MIMO refers to a planar array with a massive number of antennas that are individually controlled and densely deployed in a space-constrained factor form at the base station. Understanding the fundamentals of Holographic MIMO communications requires to take into account the mutual coupling that has been typically overlooked in the vast majority of past and recent MIMO literature. This is particularly true in the Massive MIMO literature, which is all about using physically large arrays. The aim of this talk is to shed light on the effects of mutual coupling in Holographic MIMO communications.
Biography: Prof. Luca Sanguinetti is currently an Associate Professor with the Dipartimento di Ingegneria dell’Informazione, University of Pisa. He has coauthored two textbooks: “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017) and “Foundations of User-centric Cell-free Massive MIMO” (2020). His expertise and general interests span the areas of communications and signal processing. Dr. Sanguinetti received the Marconi Prize Paper Award in Wireless Communications in 2018 and 2022, the IEEE Communications Society Outstanding Paper Award in 2023 and coauthored a paper that received the Young Best Paper Award from the ComSoc/VTS Italy Section. He served as an Associate Editor for IEEE Transactions on Wireless communications, IEEE Signal Processing Letters, and IEEE Journal on Selected Areas of Communications. He was a member of the Executive Editorial Committee of IEEE Transactions on Wireless Communications. He is currently serving as an Associate Editor for the IEEE Transactions on Communications and is a member of the Steering Committee of IEEE Transactions on Wireless Communications. He is an IEEE Senior Member.
Fredrik Tufvesson: Channel modeling for 6G
Biography: Fredrik Tufvesson was born in Lund, Sweden in 1970. He received the M.S. degree in Electrical Engineering in 1994, the Licentiate Degree in 1998 and his Ph.D. in 2000, all from Lund University in Sweden. After two years at a startup company developing mesh network technologies, Fredrik is now professor of Radio systems at the department of Electrical and Information Technology, Lund University. His main research interests are channel modelling, measurements and characterization for wireless communication, with applications in various areas such as massive MIMO, UWB, mm wave communication, distributed antenna systems, radio based positioning and vehicular communication.
Henk Wymeersch: Radio localization and sensing: the path from 5G to 6G
Biography: Henk Wymeersch is a Professor in Communication Systems with the Department of Electrical Engineering at Chalmers University of Technology, Sweden. He is also a Distinguished Research Associate with Eindhoven University of Technology (TU Eindhoven). Prior to joining Chalmers, he was a Postdoctoral Associate during 2006-2009 with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT). He obtained the Ph.D. degree in Electrical Engineering/Applied Sciences in 2005 from Ghent University, Belgium. He has served as Associate Editor for several IEEE journals and also as General Chair of the 2015 International Conference on Localization and GNSS. Awards include an ERC Starting Grant and a Chalmers supervision award. He currently leads the CROSSNET team at Chalmers.
Jakob Hoydis: Differentiable Tools for Digital Twin Networks
Abstract: A possible vision for 6G networks is that they are able to autonomously specialize to the radio environment in which they are deployed. I will discuss two key tools that are required to make this happen, namely differentiable ray tracing for the creation of digital twin networks and machine learning. Differentiable ray tracing allows for gradient based optimization of many scene parameters and enables data-driven calibration of ray tracing models to measurements. Such digital twins can then be used as “gyms” for training of environment specific communication schemes and applications. As examples, I will show how one can learn radio material parameters from channel measurements and present the architecture and performance of a recently developed 5G-compliant neural receiver which is not only compatible with different bandwidth allocations and number of layers, but could possibly be implemented in real-time.
Biography: Jakob Hoydis is a Principal Research Scientist at NVIDIA working on the intersection of machine learning and wireless communications. He is a recipient of the 2019 VTG IDE Johann-Philipp-Reis Prize, the 2019 IEEE SEE Glavieux Prize, the 2018 IEEE Marconi Prize Paper Award, the 2015 IEEE Leonard G. Abraham Prize, the IEEE WCNC 2014 Best Paper Award, the 2013 VDE ITG Förderpreis Award, and the 2012 Publication Prize of the Supéléc Foundation. He has received the 2018 Nokia AI Innovation Award, as well as the 2018 and 2019 Nokia France Top Inventor Awards. He is a co-author of the textbook “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017). He is a 2023 Distinguished Industry Speaker of the IEEE Signal Processing Society.