TUTORIAL - Marco di Renzo - mmWave RIS
Wireless Communications in the Wave Domain: Reconfigurable Intelligent Surface, Holographic MIMO, and the like

Speaker: Marco di Renzo, CNRS Research Director (Professor), Head of the Intelligent Physical Communications Group

Affiliation: L2S-CentraleSupelec, Paris-Saclay University, Paris, France

Abstract: In wireless communications, we have been recently assisting to the upsurge in brand-new technologies for the physical layer, which rely on encoding and processing information in the wave domain, i.e., at the electromagnetic level. This emerging trend has been facilitated by recent and promising advances in the field of configurable antennas, and, especially, metamaterials, and metasurfaces, which are engineered materials that can process the electromagnetic waves in the wave domain without the need of analog-to-digital and digital-to-analog conversions.

Notable examples of these emerging technologies include (i) spatial (SM), index (IM), media-based, and metasurface-based modulation, which encode information onto the physical characteristics of antennas and metasurfaces; (ii) reconfigurable intelligent surfaces (RIS), which improve the transmission of data by appropriately shaping the propagation of electromagnetic waves in the wave domain, tuning radio propagation environments into smart radio propagation environments; (iii) holographic surfaces (HoloS), which are continuous-aperture hybrid multiple-input multiple-output (MIMO) systems, where the encoding and decoding of data is performed in the wave domain; and (iv) stacked intelligent surfaces (SIM), which are multi-layer metasurface-based devices resembling deep neural networks, where the encoding and encoding of data is realized through iterative signal processing operations in the wave domain.

This tutorial is aimed at (i) introducing the benefits of wireless communications in the wave domain; (ii) presenting the key emerging technologies in this context; (iii) overviewing the state-of-the-art electromagnetically consistent communication models for wave domain communications; (iv) summarizing the most recent signal processing algorithms for optimization; and (v) reporting the most recent experimental and standardization activities in this new field of research.

Marco Di Renzo (Fellow, IEEE)

Marco Di Renzo (Fellow, IEEE) received the Laurea (cum laude) and Ph.D. degrees in electrical engineering from the University of L’Aquila, Italy, in 2003 and 2007, respectively, and the Habilitation à Diriger des Recherches (Doctor of Science) degree from University Paris-Sud (currently Paris-Saclay University), France, in 2013. Currently, he is a CNRS Research Director (Professor) and the Head of the Intelligent Physical Communications group in the Laboratory of Signals and Systems (L2S) at Paris-Saclay University – CNRS and CentraleSupelec, Paris, France. Also, he is an elected member of the L2S Board Council and a member of the L2S Management Committee. At Paris-Saclay University, he serves as the Coordinator of the Communications and Networks Research Area of the Laboratory of Excellence DigiCosme, as a Member of the Admission and Evaluation Committee of the Ph.D. School on Information and Communication Technologies, and as a Member of the Evaluation Committee of the Graduate School in Computer Science. He is a Founding Member and the Academic Vice Chair of the Industry Specification Group (ISG) on Reconfigurable Intelligent Surfaces (RIS) within the European Telecommunications Standards Institute (ETSI), where he serves as the Rapporteur for the work item on communication models, channel models, and evaluation methodologies. He is a Fellow of the IEEE, IET, and AAIA; an Ordinary Member of the European Academy of Sciences and Arts, an Ordinary Member of the Academia Europaea; and a Highly Cited Researcher. Also, he holds the 2023 France-Nokia Chair of Excellence in ICT, and was a Fulbright Fellow at City University of New York, USA, a Nokia Foundation Visiting Professor, and a Royal Academy of Engineering Distinguished Visiting Fellow. His recent research awards include the 2021 EURASIP Best Paper Award, the 2022 IEEE COMSOC Outstanding Paper Award, the 2022 Michel Monpetit Prize conferred by the French Academy of Sciences, the 2023 EURASIP Best Paper Award, the 2023 IEEE ICC Best Paper Award (wireless), the 2023 IEEE COMSOC Fred W. Ellersick Prize, the 2023 IEEE COMSOC Heinrich Hertz Award, and the 2023 IEEE VTS James Evans Avant Garde Award. He served as the Editor-in-Chief of IEEE Communications Letters during the period 2019-2023, and he is now serving in the Advisory Board.

TUTORIAL - Maxime Guillaud, Christoph Studer - Channel Charting
Wireless Channel Charting for Next-Generation Radio Access Networks

Speakers: Maxime Guillaud, Senior Researcher Inria and Christoph Studer, Associate Professor ETH Zurich

Abstract: Wireless channel charting (CC) consists of the application of dimensionality reduction and manifold learning (both methods stemming from the field of machine learning) to estimate channel state information (CSI) in wireless communication transceivers. CC is an emerging framework that enables pseudo-positioning of the transmitting devices in an abstract, low-dimensional space called “channel chart.” The extracted pseudo-position information enables infrastructure base stations or wireless access points to perform location-dependent tasks relevant to emerging wireless networks in a self-supervised manner, without requiring access to the actual user location information. Prominent application examples of CC are localization relative to points-of-interest, user equipment (UE) grouping, cell handover, UE path prediction, predictive rate control, assisted beam-finding, etc.

This tutorial will provide an overview of the burgeoning research field of CC, keeping the discussion at the intersection of machine learning, numerical optimization, channel modeling, and communication theory. The tutorial covers the basics of dimensionality reduction (including algorithmic approaches and performance metrics) and its application to CSI, in an intuitive and widely accessible manner. Experimental results will be presented, and the potential impact on future radio access networks (such as 6G) will be discussed. The tutorial also covers practical aspects such as continuous and online (real-time) learning, and distributed implementation in large networks. Finally, the tutorial will present the vision of CC as a service currently being developed within the CHIST-ERA collaborative research project CHASER (https://www.linkedin.com/company/chistera-chaser/), with our partners at Aalto University and University of Minho.

Dr. Maxime Guillaud

Dr. Maxime Guillaud is a senior researcher at Inria, the French national research institute for digital science and technology, in the MARACAS team in Lyon. He received his PhD from EURECOM in 2005. Before joining Inria in 2023, Dr. Guillaud has held research positions in both academia and industry, with Lucent Bell Laboratories (now Nokia) in the USA, the FTW research center and Vienna University of Technology in Austria, and Huawei Technologies in France. He is an expert on the physical layer of radio access networks, including transceiver algorithms, channel modeling, machine learning, and modulation design for non-coherent and multiple access communications. He has authored over 90 research papers and holds 18 patents. He is a senior member of IEEE and current ComSoc distinguished lecturer.

Website: https://maximeguillaud.github.io/


Prof. Dr. Christoph Studer

Prof. Dr. Christoph Studer is an Associate Professor at the Department of Information Technology and Electrical Engineering at ETH Zurich in Switzerland since 2020. He received his M.S. and Ph.D. degrees from ETH Zurich in 2006 and 2009, respectively. From 2009 to 2012, he was a Postdoctoral Researcher at ETH Zurich and Rice University in Houston, TX. In 2013, he was a Research Scientist at Rice University. From 2014 to 2019, he was an Assistant Professor at Cornell University, Ithaca, NY. From 2019 to 2020, he was an Associate Professor at Cornell University and at Cornell Tech. Dr. Studer’s research interests are at the intersection of wireless communications, digital signal processing, machine learning, and digital VLSI design.

Dr. Studer received ETH Medals for his M.S. and Ph.D. theses in 2006 and 2009, respectively. He received a Swiss National Science Foundation fellowship for Advanced Researchers in 2011 and a US National Science Foundation CAREER Award in 2017. He shared the Swisscom/ICTnet Innovations Award in both 2010 and 2013. Dr. Studer is currently an Associate Editor for the IEEE Open Journal of Circuits and Systems and the IEEE Transactions on Circuits and Systems II: Express Briefs. In 2019 and 2022, he was the Technical Program Chair and the General Chair of the Asilomar Conference on Signals, Systems, and Computers, respectively.

Prof. Studer was the lead inventor of Channel Charting in 2018, which was developed together with Prof. Dr. Olav Tirkkonen from Aalto University, Finland.

Prof. Studer’s research group website: https://iip.ethz.ch/



TUTORIAL - Giacomo Bacci, Luca Sanguinetti - massive MIMO
Next-Generation MIMO Communications

Speakers: Giacomo Bacci and Luca Sanguinetti

Affiliation: University of PIsa, Italy

Abstract: Massive MIMO (multiple-input multiple-output) technology, became a reality in 5G communication systems, represents a significant shift in wireless technology design. As the demand for widespread wireless access continues to grow at an exponential pace, massive MIMO can be leveraged to increase the potential of wireless systems, leading to what is known as ultra-massive MIMO. In this future situation, the arrays are dense and electrically large, to exploit all the maximum spatial degrees of freedom (DoF) for beamforming and spatial multiplexing. To support a feasible and effective system design, many issues, such as computational complexity and hardware impairments need to be properly tackled.

The first part of this tutorial covers the fundamentals of ultra-massive MIMO, including a primer on radiative near-field communications, connections between electromagnetic and information theory, and the derivation of DoF for massive spatial multiplexing. The second part focuses on adapting the classical tasks of communication systems, such as channel estimation and uplink data reception, to this new paradigm, also covering additional aspects and research directions, such as coupling issues in holographic MIMO and user-centric post-cellular, cell-free architectures.

Prof. Giacomo Bacci

Giacomo Bacci (S’07-M’09-SM’24) is a tenure-track assistant professor with the Dept. Information Engineering, University of Pisa, Italy. Prior to joining the University of Pisa (2022), he was a visiting post-doctoral research associate with Princeton University, USA (2012-2014), and a product manager for interactive satellite broadband communications at MBI Srl, Italy (2015-2021). He is the recipient of the FP7 Marie Curie International Outgoing Fellowships for career development (IOF) 2011 GRANDCRU, the Best Paper Award from the IEEE Wireless Communications and Networking Conference (WCNC) in 2013, the Best Student Paper Award from the International Waveform Diversity and Design Conference (WDD) in 2007, and the 2014 URSI Young Scientist Award. He is currently serving as an associate editor for IEEE Communications Letters and EURASIP Journal on Advances in Signal Processing (J-ASP), and as a Lead Guest Editor for EURASIP J-ASP special issue on “Advanced signal processing for sustainable and low footprint wireless communications”. He is a Senior Member of the IEEE and a Senior Member of the International Union of Radio Science.

Prof. Luca Sanguinetti

Luca Sanguinetti (S’03-M’07-SM’15) is a full professor with the Dept. Information Engineering, University of Pisa, Italy. He has co-authored two textbooks, “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017), and “Foundation of User-centric Cell-free Massive MIMO” (2021). His expertise and general interests span the areas of communications and signal processing. He has received the 2018 and 2022 IEEE Marconi Prize Paper Awards in Wireless Communications, and the 2023 IEEE Communications Society Outstanding Paper Award. He was also the co-author of a paper that received the Young Best Paper Award from the ComSoc/VTS Italy Section. He served as an Associate Editor for IEEE TWC and the IEEE JSAC (series on Green Communications and Networking) and as a Lead Guest Editor for IEEE JSAC Special Issue on “Game Theory for Networks”, as an Associate Editor for the IEEE SPL. He was also a member of the Executive Editorial Committee of the IEEE TWC. He is currently serving as an Associate Editor for the IEEE TCOM and he is a member of the Steering Committee of IEEE TWC.


Open Innovation on the Open RAN Ecosystem: Challenges, Lessons and Opportunities with Using and Extending Open Source Solutions

Speakers: Daniel Lazkani Feferman, Eduardo Melão, and João Paulo Sales Henriques Lima

Affilliations: CPDQ,Campinas-SP, Brazil

Abstract: The telecommunications landscape is transitioning towards more open, flexible, and disaggregated networks. This shift is driven by the growing demand for network scalability, flexibility, and the ability to integrate innovations from various sources, fostering a more competitive and diverse ecosystem. The advent of Open RAN (Radio Access Network) standards represents a significant milestone in this journey, promising to redefine the construction, subdivision, and interconnection of RAN components. This paradigm shift not only aims to enhance traditional performance metrics such as throughput and capacity but also introduces new dimensions of interoperability, vendor diversity, and innovation. Answering to this new challenges, the open source community mobilized to develop and
maintain a number of solutions for implementing the different Open RAN components, each focusing on a different set of requirements, providing a different set of features and way of working, and maintaining a different set of features on their roadmaps. Over the last 47 years, CPQD, a private institution employing nearly 900 people, has emerged as the largest private ICT (Information and Communication Technology) innovation center in Latin America, with significant contributions to societal development, progress, and wellbeing through its advanced ICT solutions. CPQD has been experimenting and extending a large subset of those open source solutions for Open RAN components on different projects and products, and was recently selected by the Brazilian government as the EXCellence Centre in Open Networks (EXCCON) to engage and further develop the Brazilian Open RAN ecosystem. In this tutorial, we will present the current panorama on Open RAN technologies, explain the major existing solutions based on open source initiatives, report our experiences in using and extending them, present their roadmaps for the future, and provide guidelines for the community on how to use and engage with them.

Daniel Lazkani Feferman

Daniel Lazkani Feferman is currently a Telco Cloud Architect at CPQD, working with open source tools to increase mobile connectivity considering 5G and orchestration tools. He holds a BSc. in Telecom Engineering at UFF and MSc. in Electrical and Computer Engineering at UNICAMP. In the past, he received a fully funded scholarship from the Brazilian government to study at the New York Institute of Technology (NYIT) and Former researcher at the Illinois Institute of Technology (IIT).

Eduardo Melão

Eduardo Melão obtained a BSc in Electrical Engineering at UFJF in 2021. Eduardo has almost 5 years of experience developing protocol stacks for cellular communication networks, covering from 4G to 5G protocols and OpenRAN. He started his career as an intern at CPQD, where he developed from scratch a simplified MAC Layer for the H2020 5G-RANGE project. Since then, Eduardo works as Technology Development Analyst at CPQD developing and testing open-source and proprietary solutions for 4G and 5G networks. More recently, he has been working in various OpenRAN integrations with different vendors and functional parts of OpenRAN architecture.

João Paulo Sales Henriques Lima

João Paulo Sales Henriques Lima has obtained a BSc and a MSc in Electrical Engineering at UFJF in 2018 and 2022, respectively. Currently, he is an AI Researcher engaged at AI/ML applications for mobile networks optimization, with special attention to Open RAN technology, RIC and xApps projects, at CPQD. Previously, he was with Samsung SIDIA as a Protocol Software Developer.