Prof. Emil Björnson
Royal Institute of Technology, Sweden
Prof. Luca Sanguinetti
University of Pisa, Italy
Dr. Özlem Tuğfe Demir
Royal Institute of Technology, Sweden
As the first release of 5G has recently been finalized and commercial networks have been launched, it is time to look for new forward-looking research directions that have the potential to revolutionize the future of wireless. Just as the seminal papers on Massive MIMO were published 10 years ago, this is likely the time when the key technology components for 6G will be identified. Hence, this is the right time for researchers to catch onto new research directions and potentially find the next big thing.
In this tutorial, we will first go through the foundations of the original Cell-Free Massive MIMO, which is a recently proposed alternative infrastructure to overcome the key weaknesses of cellular systems. The first papers in this area are just a few years old and there are still many open problems. One important issue with the original form of Cell-Free Massive MIMO is scalability, which is one of the key topics that we will cover in this tutorial as well as possible solutions such as user-centric dynamic cooperation clustering. We will describe different methods for signal processing and spatial resource allocation including optimized techniques and scalable heuristics solutions. After providing some implementation constraints, we will discuss open problems related to this research direction.
The presentation will be based on our recently published textbook on the topic, “Foundations of User-Centric Cell-Free Massive MIMO”, which summarizes the state-of-the-art in the field and is the first book of its kind on this emerging topic. We are also planning to provide a free PDF of this book to the conference attendees.
Emil Björnson (S’07-M’12-SM’17) is currently a Visiting professor at KTH Royal Institute of Technology, Sweden, and Associate Professor at Linköping University, Sweden. He has authored the textbooks Optimal Resource Allocation in Coordinated Multi-Cell Systems (2013), Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency (2017), and Foundations of User-Centric Cell-Free Massive MIMO (2021). He is dedicated to reproducible research and has made a large amount of simulation code publicly available. He performs research on MIMO communications, radio resource allocation, machine learning for communications, and energy efficiency. Since 2017, he has been on the Editorial Board of the IEEE Transactions on Communications and the IEEE Transactions on Green Communications and Networking since 2016. He has received the 2014 Outstanding Young Researcher Award from IEEE ComSoc EMEA, the 2015 Ingvar Carlsson Award, the 2016 Best Ph.D. Award from EURASIP, the 2018 IEEE Marconi Prize Paper Award in Wireless Communications, the 2019 EURASIP Early Career Award, the 2019 IEEE Communications Society Fred W. Ellersick Prize, and the 2019 IEEE Signal Processing Magazine Best Column Award. He also co-authored papers that received Best Paper Awards at the conferences, including WCSP 2009, the IEEE CAMSAP 2011, the IEEE WCNC 2014, the IEEE ICC 2015, WCSP 2017, and the IEEE SAM 2014.
Luca Sanguinetti (SM’15) is currently an Associate Professor with the Dipartimento di Ingegneria dell’Informazione, University of Pisa. He has coauthored the textbooks Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency (2017) and Foundations of User-Centric Cell-Free Massive MIMO (2021). His expertise and general interests span the areas of communications and signal processing. Dr. Sanguinetti was a recipient of the 2018 Marconi Prize Paper Award in Wireless Communications and coauthored an article that received the Young Best Paper Award from the ComSoc/VTS Italy Section. He was the recipient of the FP7 Marie Curie IEF 2013 “Dense deployments for green cellular networks”. He was also a co-recipient of the two best conference paper awards: IEEE WCNC 2013 and IEEE WCNC 2014. He served as an Associate Editor for the IEEE Transactions on Wireless Communications and the IEEE Journal on Selected Areas of Communications (series on Green Communications and Networking) and as a Lead Guest Editor for the IEEE Journal on Selected Areas of Communications Special Issue on “Game Theory for Networks”. He is currently serving as an Associate Editor for the IEEE Signal Processing Letters, the IEEE Transactions on Communications. He is also a member of the Executive Editorial Committee of the IEEE Transactions on Wireless Communications.
Özlem Tuğfe Demir received the B.S., M.S., and Ph.D. degrees in Electrical and Electronics Engineering from Middle East Technical University, Ankara, Turkey, in 2012, 2014, and 2018, respectively. She was a Postdoctoral Researcher with Linköping University, Sweden in 2019-2020. She is currently a Postdoc with KTH Royal Institute of Technology, Sweden. She has coauthored the textbook Foundations of User-Centric Cell-Free Massive MIMO (2021). Her research interests focus on signal processing and optimization in wireless communications, massive MIMO, beyond 5G multiple antenna technologies, deep learning, and green communications. She is a recipient of the IEEE SIU 2015 Conference Student Best Paper Award, the Best Thesis Award for M.S. Program and Graduate Courses Performance Award at the Middle East Technical University.
Prof. Marco Di Renzo
Paris-Saclay University, CNRS, France
Reconfigurable intelligent surfaces (RISs) have recently emerged as the new wireless communication research frontier with the goal of realizing metamaterial-coated smart and reconfigurable radio propagation environments through passive and tunable signal transformations. Featured by orders of magnitude lower hardware and energy cost than traditional active antenna-arrays and yet superior performance, RISs are the new driving technology for future wireless networks, especially for enabling them to migrate to higher frequency bands. RISs have the inherent potential of transforming the current wireless network with active nodes solely into a new hybrid network comprising active and passive components co-working in an intelligent way, so as to achieve a sustainable capacity growth with a low and affordable cost and power consumption. Therefore, RISs have the potential to change how wireless networks are currently designed, usher in that hoped-for wireless future, and are regarded as an enabling technology for realizing the emerging concept of metamaterial-assisted smart (programmable) radio environments (SREs). RIS-assisted SREs are a multidisciplinary research endeavor but are not well-understood. In this talk, I will introduce the state of the art, the research challenges, and some recent research results at the crossroad of wireless communications, electromagnetics, physics, and metamaterials.
Marco Di Renzo 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, France, in 2013. Since 2010, he has been with the French National Center for Scientific Research (CNRS), where he is a CNRS Research Director (CNRS Professor) in the Laboratory of Signals and Systems (L2S) of Paris-Saclay University – CNRS and Centrale Supelec, Paris, France. In Paris-Saclay University, he serves as the Coordinator of the Communications and Networks Research Area of the Laboratory of Excellence DigiCosme, and as a member of the Admission and Evaluation Committee of the Ph.D. School on Information and Communication Technologies. Currently, he serves as the Editor-in-Chief of IEEE Communications Letters, and is a Distinguished Speaker of the IEEE Vehicular Technology Society. In 2017-2020, he was a Distinguished Lecturer of the IEEE Vehicular Technology Society and IEEE Communications Society. Also, he served as an Editor and the Associate Editor-in-Chief of IEEE Communications Letters, and as an Editor of IEEE Transactions on Communications and IEEE Transactions on Wireless Communications. Currently, he serves as the Founding Chair of the Special Interest Group on Reconfigurable Intelligent Surfaces of the Wireless Technical Committee of the IEEE Communications Society, and is the Founding Lead Editor of the IEEE Communications Society Best Readings in Reconfigurable Intelligent Surfaces. He is a Highly Cited Researcher (Clarivate Analytics, 2019), a World’s Top 2% Scientist from Stanford University (2020), a Fellow of the IEEE (2020), and a Fellow of the IET (2020). He has received several individual distinctions and research awards, which include the IEEE Communications Society Best Young Researcher Award for Europe, Middle East and Africa, the Royal Academy of Engineering Distinguished Visiting Fellowship, the IEEE Jack Neubauer Memorial Best System Paper Award, the IEEE Communications Society Young Professional in Academia Award, the SEE-IEEE Alain Glavieux Award, and a 2019 IEEE ICC Best Paper Award. In 2019, he was a recipient of a Nokia Foundation Visiting Professorship for conducting research on metamaterial-assisted wireless communications at Aalto University, Finland.
Prof. Guilherme Barreto Xavier
Linköping University, Sweden
The field of quantum technologies has experienced tremendous growth in recent years motivated by the promise of a host of major improvements across several applications in Information and Communication Technology (ICT). In particular, quantum communication promises novel encryption schemes as well as providing a physical layer to connect future networks of quantum computers. In this tutorial, I will go over the basics of quantum communication and discuss how photonic quantum states can be prepared, transmitted over long distances and detected with high-fidelity. I will discuss the technology behind it, key protocols and present some recent state-of-the-art results showing where the field is headed.
Guilherme Barreto Xavier obtained the PhD degree in Electrical Engineering in 2009 at the Pontifical Catholic University in Rio de Janeiro on experimental quantum communications over optical fibers. Following a two-year postdoc period at the same university he joined the faculty at the Electrical Engineering Department at the University of Concepción in Chile as an Assistant Professor, later becoming Associate Professor in 2014. There he led or co-led important experiments in the areas of high-dimensional quantum key distribution, quantum contextuality, Bell tests based on genuine-energy-time entanglement and the use of spatial-division-multiplexing technology in quantum information, with the results published in journals such as Physical Review Letters and Nature Communications. Since 2017 he moved to Sweden, joining the faculty at the Electrical Engineering department at Linköping University as a Senior Lecturer. He started a new group focusing on research on experimental quantum information using next-generation optical fibers, and is an associate editor at Frontiers in Photonics.
Prof. Nuria González Prelcic
North Carolina State University, USA
Vehicles are becoming more intelligent and automated. To achieve higher automation levels, vehicles are being equipped with more and more sensors. High data rate connectivity seems critical to allow vehicles and road infrastructure exchanging all these sensor data to enlarge their sensing range and make better safety related decisions. This presentation explains how mmWave bands can support gigabit-per-second data rates for next generation V2X from a physical layer perspective. Special attention is paid to the current limitations of 5G, and where the opportunities lie in going beyond 5G to 6G. Approaches exploiting sensor information, deep learning, and new elements in the infrastructure as non-terrestrial networks are discussed.
Nuria González Prelcic received her Ph.D. in Electrical Engineering in 2000 from the University of Vigo, Spain. She joined the faculty at the Electrical and Computer Engineering Department in North Carolina State University as an Associate Professor in 2020. Her main research interests include signal processing theory and signal processing and machine learning for wireless communications: filter banks, compressive sampling and estimation, multicarrier modulation, massive MIMO, MIMO processing for millimeter wave communication and sensing, including vehicle-to-everything (V2X) and air-to-everything (A2X) MIMO communication. She has published more than 80 papers in the topic of signal processing for millimeter wave and massive MIMO communications, including a highly cited tutorial published in the IEEE Journal of Selected Topics in Signal Processing. She is an Editor for IEEE Transactions on Wireless Communications. She is an elected member of the IEEE Sensor Array and Multichannel Technical Committee.
Prof. Guilherme de Alencar Barreto
Federal University of Ceará, Brazil
In this tutorial we will cover the kernel versions of adaptive linear filters, such as the famous LMS and RLS filters. The kernel-based formulation makes such filters capable of handling signals generated by non-linear dynamic systems. However, it also brings considerable disadvantages, such as a considerable increase in the complexity of the filter due to the need to store all the observed samples to build the kernel matrix at each instant of time. In order to mitigate this effect, different sparsifying methods are available in the literature, in which a dictionary with a small amount of relevant samples is built over time. In this tutorial, we will discuss variants of the LMS kernel (KLMS) and RLS kernel (KRLS) filters, with an emphasis on the latter, as well as different dictionary building techniques and recent contributions in this area made in our research group. Other important concepts to be addressed in the tutorial: currentropy, robustness to outliers and tracking ability of KRLS filters. Applications in signal processing, prediction of time series and identification of dynamic systems will be presented and discussed.
Guilherme de Alencar Barreto has a bachelor degree in Electrical Engineering from the Federal University of Ceará, a master degree in Electrical Engineering from the School of Engineering of São Carlos/USP (1998) and a doctorate in Electrical Engineering, also from the School of Engineering of São Carlos/USP (2003), with a period of sandwich doctorate at the University of Bielefeld (Germany). He is an associate professor in the Department of Teleinformatics Engineering, Federal University of Ceará. His main research area is Computational Intelligence and Machine Learning with applications in robotics, identification and control of dynamic systems, and pattern recognition. He is a member of the Brazilian Society of Computational Intelligence (SBIC), having been its president in the 2015-2017 biennium, and of the Brazilian Society of Automation (SBA). He is editor-in-chief of Learning & Nonlinear Models (L&NLM) journal, published by SBIC, since 2009. He is also associate editor of Applied Intelligence (Springer), International Journal of Machine Learning and Cybernetics (Springer), International Journal of Innovative Computing and Applications (Inderscience) and Frontiers. He is currently the coordinator of the Graduate Program in Teleinformatics Engineering-PPGETI (CAPES 6), Center of Technology, Federal University of Ceará.
Prof. Renato Machado
Aeronautics Institute of Technology (ITA), Brazil
Prof. Diego da Silva de Medeiros
Federal Institute of Santa Catarina (IFSC), Brazil
Msc. Rômulo Fernandes da Costa
Aeronautics Institute of Technology (ITA), Brazil
Over the Horizon (OTH) Radar, also known as High Frequency (HF) Radar, is one of the best technologies for long-range maritime surveillance. HF signals can reach a far range of up to 4,000 km using ionospheric propagation at a relatively low cost. Among HF radar applications are the detection of ocean currents, eddies, and tsunamis, in addition to maritime surveillance, missile detection, and tracking of stealth targets. Brazil is the first country in South America to have an OTH radar system installed for monitoring its coastline. The system is operated by the IACIT company, located in São José dos Campos, São Paulo. In this context, this tutorial aims to make an introduction to radar signal processing, with emphasis on OTH radars, focusing on signal modeling and noise and interference mechanisms, as well as simulation of a complete system.
Renato Machado received the B.S.E.E. degree from the São Paulo State University (UNESP), Ilha Solteira, SP, Brazil, in 2001. He received the M.Sc. and Ph.D. degrees in Electrical Engineering from the Federal University of Santa Catarina (UFSC), Florianópolis, SC, Brazil, in 2004 and 2008, respectively. From November 2013 to February 2015, Dr. Machado was a visiting Research Fellow at Blekinge Institute of Technology (BTH) in partnership with Saab AB. From August 2009 to December 2017, he was an Assistant (2008-2016) and an Associate (2017) Professor at the Federal University of Santa Maria, RS, Brazil, where he lectured many courses to bachelor and graduate programs and assumed different positions in the institution, namely, Researcher leader of the Communications and Signal Processing Research Group, Coordinator of the Telecommunications Engineering Program, and Director of the Aerospace Science Laboratory. Since December 2017, Dr. Machado has been with the Aeronautics Institute of Technology (ITA) as an Associate Professor. He is the Research leader of the Digital and Signal Processing Laboratory, ITA, and SAR and Radar Signal Processing Laboratory, ITA. In February 2021, Dr. Machado received the Senior Membership degree from the Institute of Electrical and Electronics Engineers (IEEE). His research interests include SAR Processing, SAR Image Processing, Change Detection, Radar Signal Processing, and Digital Signal Processing.
Diego da Silva de Medeiros is a Professor from the Telecommunications Department of Federal Institute of Santa Catarina (IFSC). He has an undergraduate course in Telecommunications Systems at the Federal Center of Technological Education of Santa Catarina (2008 – CEFET-SC) and a Master’s degree in Electrical Engineering at the Federal University of Santa Catarina (2013 – UFSC). Currently, he is doing his doctorate in the Graduate Program in Electronic Engineering and Computing, area of Telecommunications (PG/EEC-T), at Technological Institute of Aeronautics (ITA). His research interests are Signal Processing, Telecommunications Systems, acting mainly in the following themes: beamforming, image processing, and radar signal processing.
Rômulo Fernandes da Costa received the Bachelor Engineering degree in Electrical Engineering (with an emphasis in Electronics) from the São Paulo State University (UNESP), Brazil, in 2015, and received the Master degree in Electronics and Computer Engineering from the Aeronautics Institute of Technology (ITA), Brazil, in 2019. He is currently working toward the Ph.D. degree in Electronics and Computer Engineering at ITA. His research interests include robotics, signal processing, mathematical modeling, control and simulation of dynamic systems, and artificial intelligence.
Prof. José Eduardo Souza de Cursi
Institut National des Sciences Appliquées (INSA) in Rouen, France
Uncertainty quantification (UQ) is a collection of numerical techniques for the characterization of the variability of the response of systems subject to random phenomena or affected by errors. The methods proposed by UQ are quite generic and can meet the needs of various areas of knowledge. For example, there are applications in the literature to Mechanical Engineering, Biology, Transportation, Communications, game theory, climatology, …
In this introductory short course, we will cover the fundamental techniques of representing variability and show how to use these fundamental techniques to determine probability distributions and analyze events associated to systems whose responses can be modeled by optimization problems, differential equations, linear systems, algebraic equations. We will also look at the case of curves and surfaces such as Pareto fronts and limit state curves connected to failure probabilities.
Basic knowledge of probability and numerical methods will be enough to be able to follow the short course.
Prof. Eduardo Souza de Cursi is B.Sc. in Physics from the University of São Paulo (1978) and M.Sc. in Physics from the Centro Brasileiro de Pesquisas Físicas (1980). He is also Docteur ès Sciences from the Université Des Sciences Et Techniques Du Languedoc (1990). He is currently a full professor (classe exceptionnelle) at the Institut National des Sciences Appliquées de Rouen. He was Director of International Relations at INSA Rouen, Director of the Department of Mechanics at INSA Rouen, Director of the DEA “Modélisation, Contrôle et Optimisation”, Director of the DEA “Sciences de l’Ingénieur”, Interim Director of the Department of Civil Engineering and Durable Constructions at INSA Rouen. He was in charge of several missions at INSA Rouen Normandie and within the INSA Group: creation of the Centre Régional d’Usinage Grande Vitesse, Construction of the Institut de Mécanique de Rouen, creation of the Civil Engineering Department, creation of the International Relations Committee of the INSA Group, Délégué aux Relations Européennes et Internationales du Groupe INSA, director of the Laboratoire de Mécanique de Rouen, director of the Laboratoire d’Optimisation et Fiabilité en Mécanique des Structures. He is currently director of the Laboratoire de Mécanique de Normandie, directeur stratégique de Relations Européennes et Internationales de l’INSA de Rouen, head of the French-Dominican program for training Dominican engineers in France. He was one of the members of the French commission for the implementation of the program of graduação-sanduíche and for the creation of the BRAFITEC program. He is also the creator of the CALIOPE program with the Dominican Republic. He has experience in Applied Mathematics and Theoretical Mechanics, with emphasis on Numerical Analysis, Stochastic Methods and Convex Analysis.