SPAWC21 is hosting 8 live-streamed tutorials focusing on timely topics in signal processing for wireless communications.
T1 – Wireless Federated Learning
Speakers: Deniz Gunduz (Imperial College London, UK) and Wojciech Samek (Fraunhofer Heinrich Hertz Institute, Germany).
Abstract
Deep neural networks have achieved incredible success in solving complex tasks. Today’s models are trained on millions of examples and are able to reliably annotate images, translate text, understand spoken language or play strategic games such as chess or Go. At the same time the number of intelligent devices on wireless networks (e.g. smartphones, IoT devices) has rapidly grown. These devices are equipped with sensors and with increasingly powerful processors that allow them to collect and process data at unprecedented levels. This development provides a unique opportunity for deep learning methods to revolutionize wireless applications and services, bringing intelligence to the edge. However, due to limited wireless resources (e.g., bandwidth and power), latency constraints, and data privacy concerns, centralized training is often not viable in the wireless setting. Instead, wireless devices collaborate to jointly train a model without any of the participants having to reveal their local data to other parties or to a centralized server. This new form of “federated training” concentrates learning in locations where the models are actually used (i.e., at the network edge); and thus, minimizes latency and resource consumption, and limits privacy leakage.
The objective of this tutorial is to introduce the fundamental concepts and methods in federated learning, and to discuss the challenges and benefits of their application in wireless networks. The tutorial will not only provide a theoretical understanding and overview related concepts from information theory, optimization, and wireless communications, but also discuss certain tricks (e.g., error accumulation, synchronization, client clustering, over-the-air computation) to improve the performance in practice. Furthermore, we will present the recent developments and trends, in particular the applications of federated learning to wireless networks, and a summary of relevant standardization activities.
Deniz Gunduz
Deniz Gunduz is a Professor of Information Processing in the Electrical and Electronic Engineering Department of Imperial College London, UK, where he leads the Information Processing and Communications Laboratory, and serves as the deputy head of the Intelligent Systems and Networks Group. He is also a part-time faculty member at the University of Modena and Reggio Emilia, Italy, and has held visiting positions at University of Padova (2018-2020) and Princeton University (2009-2012). His research interests lie in the areas of communications and information theory, machine learning, and privacy. Dr. Gündüz is a Distinguished Lecturer for the IEEE Information Theory Society (2020-22), and serves as an Area Editor for the IEEE Transactions on Communications and the IEEE Journal on Selected Areas in Communications (JSAC), and as an Editor of the IEEE Transactions on Wireless Communications. He is a co-editor of the book “Machine Learning and Wireless Communications” soon to be published by the Cambridge University Press.
Wojciech Samek
Wojciech Samek is head of the Department of Artificial Intelligence and the Explainable AI Group at Fraunhofer Heinrich Hertz Institute (HHI), Berlin, Germany. He studied computer science at Humboldt University of Berlin, Heriot-Watt University and University of Edinburgh from 2004 to 2010 and received the Dr. rer. nat. degree with distinction (summa cum laude) from the Technical University of Berlin in 2014. After his PhD he founded the Machine Learning Group at Fraunhofer HHI, which he has directed until 2020. Dr. Samek is associated faculty at the Berlin Institute for the Foundation of Learning and Data (BIFOLD), the ELLIS Unit Berlin and the DFG Graduate School BIOQIC. He is recipient of multiple best paper awards, including the 2020 Pattern Recognition Best Paper Award, and part of the MPEG-7 Part 17 standardization. He is co-editor of the Springer book “Explainable AI: Interpreting, Explaining and Visualizing Deep Learning”. Dr. Samek has co-authored more than 150 peer-reviewed journal and conference papers; some of them listed by Thomson Reuters as “Highly Cited Papers” (i.e., top 1%) in the field of Engineering.
T2 – Quantum Information Processing: An Essential Primer
Speakers: Emina Soljanin (Rutgers University, USA).
Abstract
Quantum information science is an exciting, broad, rapidly progressing, cross-disciplinary field, and that very nature makes it both attractive and hard to enter. This tutorial will first provide answers to the three essential questions that any newcomer needs to know: How is quantum information represented? How is quantum information processed? How is classical information extracted from quantum states? We will then introduce the most fundamental quantum algorithms and protocols that illustrate quantum computing advantages. The tutorial will conclude with examples that demonstrate the power of quantum correlations. No prior knowledge of quantum mechanics is assumed.
Emina Soljanin
Emina Soljanin is a professor of Electrical and Computer Engineering at Rutgers. Before moving to Rutgers in January 2016, she was a (Distinguished) Member of Technical Staff for 21 years in various incarnations of the Mathematical Sciences Research Center of Bell Labs. Her interests and expertise are broad, currently ranging from distributed computing to quantum information science. She is an IEEE Fellow, an outstanding alumnus of the Texas A&M School of Engineering, the 2011 Padovani Lecturer, a 2016/17 Distinguished Lecturer, and the 2019 President for the IEEE Information Theory Society.
T3 – Reconfigurable Intelligent Surfaces for Future Wireless Communications
Speakers: Alessio Zappone (University of Cassino, Italy) and Marco di Renzo (CNRS, France).
Abstract
As 5G networks take their final form, connectivity demands continue to increase exponentially and new services pose more constraints on the performance that end-users expect. A recent technological breakthrough that holds the potential to meet these demands is that of reconfigurable intelligent surfaces. This tutorial describes the fundamental principles and latest results of reconfigurable intelligent surfaces for beyond 5G wireless communications.
Alessio Zappone
Alessio Zappone is a tenured professor at the university of Cassino and Southern Lazio, Italy. He was appointed exemplary reviewer for the IEEE TRANSACTIONS ON COMMUNICATIONS and IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS in 2017. Alessio is an IEEE Senior Member, serves as senior area editor for the IEEE SIGNAL PROCESSING LETTERS and as guest editor for the IEEE JOURNAL ON SELECTED AREAS ON COMMUNICATIONS (Special Issues on Energy-Efficient Techniques for 5G Wireless Communication Systems and on Wireless Networks Empowered by RIS).
Marco Di Renzo
Dr. Marco Di Renzo is Associate Professor with Paris-Saclay University – CNRS, CentraleSupelec, Univ. Paris Sud, France. He is a Distinguished Visiting Fellow of the Royal Academy of Engineering (UK), and co-founder of the university spin-off company WEST Aquila s.r.l., Italy. Dr. Di Renzo received the THALES Communications fellowship (2003-2006), the 2012 IEEE CAMAD, 2014 IEEE CAMAD, 2014 IEEE ATC, 2015 IEEE ComManTel Best Paper Awards; the 2012 and 2014 IEEE WIRELESS COMMUNICATIONS LETTERS Exemplary Reviewer Certificate; the 2013 IEEE- COMSOC Best Young Researcher Award for Europe, Middle East and Africa; the 2015-2018 CNRS Award for Excellence in Research and in Advising Doctoral Students; the 2017 IEEE- SEE Alain Glavieux Award. He serves as Editor in Chief of the IEEE COMMUNICATIONS LETTERS and Editor of the IEEE TRANSACTIONS ON COMMUNICATIONS. He is an IEEE Fellow and a Distinguished Lecturer of the IEEE Communications and IEEE Vehicular Technology Societies.
T4 – Signal Processing for THz Communications and Sensing
Speakers: Sundeep Rangan (New York University, USA).
Abstract
The use of wireless frequencies above 100 GHz has attracted considerable interest for both massive bandwidth communication links and very high resolution RADAR and sensing.
However, systems in these frequencies have unique characteristics in terms of device nonlinearities, MIMO architectures and radio propagation that in turn present significant design challenges. This tutorial will provide an overview of recent results in the field in both the upper millimeter wave and THz frequencies from a signal processing perspective. The tutorial will be divided into five parts:
(1) Use cases and requirements;
(2) THz devices and signal processing models for nonlinearities and power consumption;
(3) Channel modeling from both ray tracing and measurements;
(4) System studies and initial feasibility results; and
(5) Future work and research perspectives.
The tutorial is intended for researchers interested in the field to help identify new research problems and directions.
Sundeep Rangan
Sundeep Rangan received the B.A.Sc. at the University of Waterloo, Canada and the M.Sc. and Ph.D. at the University of California, Berkeley, all in Electrical Engineering. He has held postdoctoral appointments at the University of Michigan, Ann Arbor and Bell Labs. In 2000, he co-founded (with four others) Flarion Technologies, a spin off of Bell Labs, that developed Flash OFDM, one of the first cellular OFDM data systems and pre-cursor to 4G systems including LTE and WiMAX. In 2006, Flarion was acquired by Qualcomm Technologies where Dr. Rangan was a Director of Engineering involved in OFDM infrastructure products. He joined the ECE department at NYU Tandon (formerly NYU Polytechnic) in 2010. He is a Fellow of the IEEE and Director of NYU WIRELESS, an academic-industry research center researching next-generation wireless systems. His research interests are in wireless communications, signal processing, information theory and control theory.
T5 – Integrated Sensing and Communication for 6G: From Theory to Applications
Speakers: Fan Liu (Southern University of Science and Technology, China) and Christos Masouros (University College London, UK) and .
Abstract
Jointly suggested by recent advances from wireless communications and signal processing, radio sensing functionality can be integrated into 6G RAN by slightly modifying the standards and signal processing strategies. This type of research is typically referred to as Integrated Sensing And Communication (ISAC), which refers to the design paradigm and corresponding enabling technologies that combine sensing and communication systems to utilize wireless resources efficiently and even to pursue mutual benefits.
In this tutorial, we will firstly overview the background and application scenarios of ISAC. As a step further, we will introduce the state-of-the-art research progress on this topic, which consists of 3 technical parts: 1) Spectral Coexistence for Sensing and Communication Systems, 2) Co-design for ISAC Systems, and 3) ISAC for V2X Networks. Finally, we will conclude the tutorial by summarizing the future directions and open problems in the area of ISAC.
Fan Liu
Fan Liu (Member, IEEE) is currently an Assistant Professor of the Department of Electrical and Electronic Engineering, Southern University of Science and Technology (SUSTech). He has previously held academic positions in the University College London (UCL), firstly as a Visiting Researcher from 2016 to 2018, and then as a Marie Curie Research Fellow from 2018 to 2020. He was the recipient of the Best Ph.D. Thesis Award of Chinese Institute of Electronics in 2019, the Marie Curie Individual Fellowship in 2018, and has been named as an Exemplary Reviewer for several IEEE Journals. He is an Associate Editor of the IEEE Communications Letters, a Lead Guest Editor of the IEEE Journal on Selected Areas in Communications (JSAC) Special Issue on “Integrated Sensing and Communications (ISAC)”, and a Founding Member of the IEEE Wireless Communications Technical Committee (WTC) Special Interest Group (SIG) on ISAC. His research interests include ISAC, vehicular network and intelligent transportation, and mmWave communications.
Christos Masouros
Christos Masouros (Senior Member, IEEE) is currently a Professor in Dept. Electrical and Electronic Engineering, University College London. His research interests lie in the field of wireless communications and signal processing. He was the recipient of the Best Paper Award in the GLOBECOM 2015 and the WCNC 2019, and has been named an Exemplary Editor for IEEE Communications Letters, and an Exemplary Reviewer for IEEE Transactions on Communications. He is an Editor for IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, the IEEE Open Journal of Signal Processing, and Editor-at-Large for IEEE Open Journal of the Communications Society, and was Associate Editor for the IEEE Communications Letters.
T6 – Goal-oriented Communication for Networked Intelligent Systems
Speakers: Marios Kountouris (EURECOM, France) and Nikolaos Pappas (Linkoping University, Sweden).
Abstract
Wireless networks are evolving to cater to emerging cyber-physical and mission-critical interactive systems, such as swarm robotics, self-driving cars, and smart Internet of Things. A fundamental shift in thinking is necessary to satisfy the requirements for real-time communication, autonomous decision-making, and efficient distributed processing.
The objective of this tutorial is to introduce the fundamental concepts, tools, and methods in goal-oriented communication. We present a paradigm shift that aims at redefining importance, timing, and effectiveness in future networked intelligent systems. We highlight key functionalities required for reliably conveying only information that is timely and valuable for achieving end users’ goals. We also discuss the potential and the challenges associated with this promising avenue of research.
Marios Kountouris
Marios Kountouris is a Professor and Chair PI on Advanced Wireless Systems at the Communication Systems department, EURECOM, France. Prior to joining EURECOM, he has held positions at CentraleSupélec, France, Huawei Paris Research Center, France, the University of Texas at Austin, USA, and Yonsei University, S. Korea. He obtained the diploma degree in electrical and computer engineering from National Technical University of Athens (NTUA), Greece in 2002 and the M.S. and Ph.D. degrees in electrical engineering from Télécom Paris, France in 2004 and 2008, respectively. He has received several career and best paper awards, including an ERC Consolidator Grant in 2020, the IEEE ComSoc CTTC Early Achievement Award and Outstanding EMEA Young Researcher Award in 2016 and 2013, respectively.
Nikolaos Pappas
Nikolaos Pappas is an Associate Professor in the Department of Science and Technology, Linköping University, Sweden. He received his B.Sc., M.Sc, and Ph.D. degrees in computer science from the University of Crete, Greece, in 2005, 2007, and 2012, respectively. He received a B.Sc. degree in mathematics from the University of Crete in 2012. He is currently an Editor for IEEE Transactions on Communications, IEEE/KICS Journal of Communications and Networks, IEEE Open Journal of the Communications Society, and a Guest Editor for the IEEE Internet of Things Journal.
T7 – Cellular UAV and Satellite Communications
Speakers: Giovanni Geraci (University Pompeu Fabra, Spain) and Adrian Garcia-Rodriguez (Huawei France R&D, France).
Abstract
Drones—a.k.a. UAVs—are taking over many processes requiring efficient, automated, and flexible machines. For their whole ecosystem to take off, the wireless community is trying to address the fundamental challenge of providing reliable cellular service to this new class of mobile devices in both 5G and the future 6G networks. Simultaneously, the cellular communications industry is taking one step upward to the sky: integrating satellite communications in next-generation mobile networks with the ultimate goal of providing anything, anytime, anywhere connectivity. This trend is being followed closely by academia, with a tremendous effort in designing and optimizing the integrated terrestrial and non-terrestrial cellular network of tomorrow. In light of the unprecented interest in this field, this one-of-a-kind tutorial blends our academic and industrial views to take a holistic approach to UAV and satellite cellular communications.
Giovanni Geraci
Giovanni Geraci (SM’19) is an Assistant Professor at University Pompeu Fabra in Barcelona, and the coordinator of the Telecommunications Engineering degree. He was previously a Research Scientist with Nokia Bell Labs and holds a Ph.D. from UNSW Sydney. He also held research appointments at SUTD in Singapore, UT Austin in the USA, CentraleSupelec in France, and Alcatel-Lucent in Italy. He serves as an IEEE ComSoc Distinguished Lecturer, an Editor for the IEEE TWC and IEEE COMML, and the IEEE ICC’22 Wireless Comm. Symposium co-Chair. He is co-inventor of a dozen patents, has written for the IEEE ComSoc Tech. News, and received international press coverage. He received the Nokia Bell Labs Ireland Certificate of Outstanding Achievement, the IEEE ComSoc EMEA Outstanding Young Researcher Award, and the IEEE PIMRC’19 Best Paper Award.
Adrian Garcia-Rodriguez
Adrian Garcia-Rodriguez (M’16) is a Senior Research Engineer at Huawei Technologies R&D (France). He received the Ph.D. degree in Electrical and Electronic Engineering from University College London (U.K.), and he was a Research Scientist at Nokia Bell Labs (Ireland) in 2016-2020. Adrian is a co-inventor of 27 patent families, for which he received the Nokia Bell Labs Ireland Certificate of Outstanding Achievement for the highest number of filed patents in 2019, and has co- authored 40+ IEEE publications on wireless communications and networking with 1k+ citations.
T8 – Wireless Channel Charting for Massive MIMO
Speakers: Maxime Guillaud (Huawei Technologies, France) and Christoph Studer (ETH Zurich, Switzerland).
Abstract
Channel charting is an emerging framework that enables pseudo-positioning of user equipments (UEs) from channel state information (CSI) only. More concretely, channel charting associates CSI to UE spatial location by means of dimensionality reduction and manifold learning, thus enabling the infrastructure base-stations or wireless access points to perform a number of predictive tasks relevant to emerging wireless networks that depend on UE location. Prominent application examples are localization relative to points-of-interest, UE grouping, cell handover, UE path prediction, predictive rate control, assisted beam-finding, etc. The goal of this tutorial is to provide the audience with an exhaustive overview of the nascent research field of channel charting, which is at the intersection of machine learning, numerical optimization, channel modeling, and communication theory. To this end, this tutorial will (i) introduce a wide range of theoretical and algorithm-level concepts, and (ii) demonstrate its efficacy with real-world results from indoor as well as outdoor Massive MIMO channel measurements.
Maxime Guillaud
Dr. Maxime Guillaud is a researcher in Huawei Technologies’ Mathematical and Algorithmic Research Lab in Paris, where he heads the signal and information processing group. He has 20 years expertise in the domain of wireless communications, in both academic and industrial research environments. He received his Ph.D. in 2005 from EURECOM, France, and previously held positions at Vienna University of Technology, FTW Telecommunications Research Center Vienna, and Bell Labs. He is an expert in the physical layer of modern wireless communications systems, and has made contributions to channel modeling and reciprocity calibration, Massive MIMO, and more. He has published over 80 journal and conference papers, and holds 8 patents. He is a Senior Member of IEEE and an Associate Editor for the IEEE Transactions on Wireless Communications.
Christoph Studer
Prof. Dr. Christoph Studer is an Associate Professor at ETH Zurich, Zurich, Switzerland. In 2013, he held the position of Research Scientist at Rice University. From 2014 to 2019, Prof. Studer has been an Assistant Professor at Cornell University and an adjunct Assistant Professor at Rice University, TX. From 2019 to 2020, Prof. Studer has been an Associate Professor at Cornell University in Ithaca, NY, and at Cornell Tech in New York, NY. Since Summer 2020, he has been an Associate Professor at the Department of Information Technology and Electrical Engineering at ETH Zurich. Prof. Studer’s research interests are in the design and analysis of algorithms and hardware designs for future multi-antenna wireless communication systems. Prof. Studer was the lead inventor of Channel Charting in 2018, which was developed together with Prof. Olav Tirkkonen from Aalto University, Finland.