Signal Processing, Waveform Optimization and Reinforcement Learning for Integrated Sensing and Communication Systems
Visa Koivunen, Aalto University, Finland

Abstract: Integrated Sensing and Communications Systems (ISAC) sense radio frequency spectrum and transfer wireless data jointly. They operate in a shared and congested, possibly even contested–spectrum with the goal of improving both communications and radar performances. We are considering ISAC systems that cooperate or are co-designed for mutual benefits. Co-designed systems may share waveforms, hardware, and antenna resources. Moreover, awareness about channel state and interference is typically exchanged. The ISAC systems have a number of degrees of freedom (DoF) and operational parameters that can be selected or adjusted to optimize their performance either by using structured optimization or machine learning. Examples of such parameters are frequency band, beampatterns, antenna selection, the modulation method, precoder–decoder designs, and power allocation. We focus on multicarrier waveforms used by most current and emerging wireless communication systems. Similarly, multicarrier waveforms have been employed for radar purposes. Radars have a variety of tasks such as target detection, tracking, parameter estimation and recognition with different objectives. We will present waveform optimization, reinforcement learning, interference management and signal processing methods for co-designed ISAC systems that share channel and interference awareness. Model-based reinforcement learning approach is taken to exploit the rich structural knowledge of man-made communication and sensing systems and radio wave propagation. Optimizing operational parameters can be modeled as a radar-centric or communications-centric constrained optimization problem where the minimum desired performance levels for other sub-systems impose the constraints. The developed OFDM radar algorithms in ISAC can take advantage of nonidealities such as carrier offsets and phase noise that are commonly considered an impairment in wireless communications. We demonstrate the achieved performance gains in different sensing and communication tasks and interference management through extensive simulation and analytical results.

 Visa Koivunen (IEEE Fellow, EURASIP Fellow) received his   D.Sc. degree in electrical engineering with honors from the   Univ of Oulu, Finland. He received the primus doctor award   among the doctoral graduates in years 1989-1994. He is a   member of Eta Kappa Nu. He was a visiting researcher at the   Univ of Pennsylvania, Philadelphia, USA, 1991-1995. Since   1999 he has been a full Professor of Signal Processing at Aalto University (formerly Helsinki UT), Finland. He received the Academy professor position in 2010 and Aalto Distinguished professor in 2020. Years 2003-2006 he was also adjunct full professor at the Univ. of Pennsylvania, USA. During his sabbatical terms in 2006-2007 and 2013-2014 he was a visiting faculty at Princeton University. He has also been a Visiting Fellow at Nokia Research (2006-2012). Since 2010 he has been part time visiting fellow and has spent mini-sabbaticals at Princeton University each year.
Dr. Koivunen’s research interest include statistical signal processing, wireless comms, radar, multisensor systems and machine learning. He has published more than 450 papers in international scientific conferences and journals and holds 5 patents. He has co-authored multiple papers receiving the best paper award in IEEE and other conferences. He was awarded the IEEE SP Society best paper award for the year 2007 (with J. Eriksson) and 2017 (w Zoubir, Muma and Chakhchouk). He was awarded the 2015 EURASIP (European Association for Signal Processing) Technical Achievement Award for fundamental contributions to statistical signal processing and its applications in wireless communications, radar and related fields. He is serving in the editorial board for Proceedings of the IEEE. He has served in the IEEE Fourier Award, Kilby Medal and Fellow Evaluation committees, SPS Award Board, IEEE AESS Radar Systems Panel and the Board of Governors for Asilomar conferences as well as IEEE SP Society Distinguished Lecturer in 2015-2016.

 

 

Future 3-Dimension Communications: Array Processing for Integrated Satellite-Terrestrial Communications
Ana Isabel Pérez-Neira, Centre Tecnològic de Telecomunicacions de Catalunya, Spain

Abstract: How do you imagine the future communication networks? Which are going to be their enabling new technologies: holographic arrays, quantum communications? Trying to answer these and related questions, researchers worldwide have begun to study new avenues, because the future networks are expected to be a wise combination of disruptive technologies and improved existing ones in 5G. Can you imagine a user centric network that you can activate whenever and wherever you are? A network with distributed intelligence and memory, that is able to transmit at terabits per second and to carry out fast computing over the air, in order to automate decisions and to enable a sustainable and always-best-connected network? You should not think only about big cities, but also about small villages, ad-hoc communities, oceans, … Such a vision is only possible if terrestrial and satellite communications become just one. We are most familiar with terrestrial radio communications, but what about satellite communications? When and where are they used? How do they operate? This talk brings satellite communications (satcom) closer to the audience with a combination of tutorial description and new avenues for research focused on the role of array processing at the physical and access layer. This will pave the way towards a new communication paradigm that allows terrestrial and satellite segments to better integrate into a 3D network.

Ana Pérez-Neira (aperez@cttc.es) is full professor at   Universitat Politècnica de Catalunya inthe Signal Theory and   Communication department since 2006 and was Vice rector     for Research (2010-14). Currently, she is the Director of   Centre Tecnològic de Telecomunicacions de Catalunya,   Spain.  Her research is in signal processing for   communications, focused on satellite communications. She has more than 60 journal papers and 300 conference papers. She is co-author of 7 books. She has leaded more than 20 projects and holds 8 patents. She is the coordinator of the Networks of Excellence on satellite communications, financed by the European Space Agency: SatnexIV-V. She has been associate editor of the IEEE TSP and EURASIP SP and ASP. Currently she is senior area editor of IEEE OJSP. She is member of the BoG of the IEEE SPS and Vice-President for conferences (2021-23). She is IEEE Fellow, EURASIP Fellow, and member of the Real Academy of Science and Arts of Barcelona (RACAB). She is recipient for the 2018 EURASIP Society Award and she has been the general chair of IEEE ICASSP’20 (the first big IEEE virtual conference held by IEEE with more than 15.000 attendees). In 2020, she has been awarded the ICREA Academia distinction by the Catalan government.

 

 

The Twin Transition and how to address the challenge of data volume inflation
Morten Dalsmo, SINTEF Digital

Abstract: The Green Transition is the combined efforts of the global community to move towards a sustainable society and combat the effects of climate change. This will impact all facets of our society, and require bold political, societal, and technological change to succeed. The EU has responded with a “European Green Deal”: a set of policy initiatives with the main goal to make EU climate neutral by 2050. To highlight the need for digital technologies, the European Commission has stated: “There is no Green Deal without digital”. The strong link between the Green and Digital Transition, also called “The Twin Transition”, lies at the heart of the strategy and research activities at SINTEF Digital. We conduct research and innovation in digital technologies and technology-oriented social sciences. Covering the entire digital value chain from advanced sensors to big data and AI, our strategy contains prioritized areas of research that directly addresses the challenges of the Twin Transition.
In this keynote, we focus on research activities in SINTEF Digital that target the specific challenges that stem from the exponential growth of sensors, sensor data and advanced signal processing. Examples from ongoing research activities are presented along with the role of SINTEF Digital as a partner for research, development, and innovation. From local involvement with start-ups and SMEs, to international collaboration with academic peers, we strive to stay ahead in the rapidly evolving research areas of digital sciences.

Morten Dalsmo is Executive Vice President of SINTEF and   Head of SINTEF Digital. SINTEF Digital conducts research and innovation in digital technologies, social sciences, and health. The institute has 480 employees and locations in Trondheim, Steinkjer and Oslo. Dalsmo has for over 20 years worked with R&D, deliveries and sales of advanced automation and IT solutions. He joined SINTEF in 2016 leaving a position as Industry Client Leader & Executive in IBM, where he started out as the global leader for IBM’s upstream petroleum business, , and later became responsible for a strategic industry client Before joining IBM, Dalsmo was with ABB for 16 years. First as a scientist and later assistant research manager at ABB Corporate Research AS, then as senior advisor, product manager, section manager and department manager in ABB AS. From 2008 to 2012, Dalsmo headed ABB’s Integrated Operations Unit. In 2017 Dalsmo led the steering group for Digital21, which was appointed by the Ministry of Trade and Industry. Digital21 has outlined a strategy to give Norwegian business and industry a digitalization boost (digital21.no). Dalsmo sits on the board of DigitalNorway – Toppindustrisenteret AS and the Faculty of Information Technology and Electrical Engineering at NTNU. Morten Dalsmo has a doctorate degree in Engineering Cybernetics from NTNU in 1997 and a master’s degree in the same field from NTH.







Ensuring Trust in the Digital Age
Jon Arne Glomsrud, DNV, Norway

Abstract: The talk will be around Assurance in the Digital Age, based on a new position paper from DNV: The accelerating deployment of digital technologies into all facets of life is transforming industries and society. Digital transformation is opening up new forms of innovation and business models; it is empowering consumers, and providing capabilities to tackle decarbonisation, climate resilience, and other sustainability challenges. While delivering value to human beings at unprecedented scale and speed, digital transformation is also creating serious new risks and uncertainties.Businesses and their stakeholders are increasingly in need of assurance that their digital assets, processes, and infrastructure will work as intended and without undesired side effects. The talk sets out a framework for how that assurance can best be provided and explores the topic of assurance in the digital age.

Jon Arne Glomsrud, MSc in Engineering Cybernetics, NTNU 1996, is a senior principal researcher in the Digital Assurance Research Center in the Future of Digital Assurance program of DNV Group Research and Development.  He has varied experience in defence, underwater and maritime technology, in both engineering and management positions, with focus on project and quality management.  He joined in 2007 Marine Cybernetics which in 2014 was acquired by DNV GL and which established Hardware-In-the-Loop testing in the maritime industry.  He has in the recent years focused on Assurance of Digital Assets, including autonomous, intelligent and complex systems, safety and security analysis using STAMP/STPA, simulation-based verification and assurance of AI.

 

Wideband Dual-Function Radar Communication Systems
Athina Petropulu, Rutgers University

Abstract: With today’s technology, radio frequency front-end architectures are very similar in radar and wireless communication systems. Further, in an effort to access more bandwidth, wireless systems have been shifting to frequency bands that have been traditionally occupied by radar systems. Given the hardware and frequency convergence, there is a lot of recent interest in the integration of the radar and communication functions in one system. Such integration will enable more efficient use of spectrum, reduce device size/cost and power consumption, and will also offer the potential for significant performance enhancement of both sensing and communication functions. Dual Function Radar-Communication (DFRC) systems is a class of integrated sensing-communication (ISC) systems that use the same waveform as well as the same hardware platform for both sensing and communication purposes. Thus, DFRC systems can achieve higher spectral efficiency than most ISC systems, require simpler transmitter hardware and a smaller, less expensive device. DFRC systems are prime candidates for autonomous driving vehicles, unmanned aerial vehicles, surveillance, search and rescue, and networked robots in advanced manufacturing applications that rely on censing and communications. In the talk, we will present a novel DFRC system that uses the available bandwidth efficiently for both communication as well as sensing. The system transmits wideband, orthogonal frequency division multiplexing (OFDM) waveforms and allows the transmit antennas to use subcarriers in a shared fashion. When all subcarriers are used in a shared fashion, the proposed system achieves high communication rate, while its sensing performance is limited by the size of the receive array. By reserving some subcarriers for exclusive use by transmit antennas (private subcarriers), the communication rate can be traded off for improved sensing performance. The improvement is achieved by using the private subcarriers to construct a large virtual array that yields higher resolution angle estimates. The system is endowed with beamforming capability, via waveform precoding, where the precoding matrix is optimally designed to meet a joint sensing-communication system performance metric. We also present novel hybrid analog-digital architectures for achieving good performance with reduced hardware and energy cost via the use of double-phase shifters.

Athina P. Petropulu is Distinguished Professor at the Electrical and Computer Engineering (ECE) Department at Rutgers, having served as chair of the department during 2010-2016.  Prior to joining Rutgers she was a Professor of ECE at Drexel University (1992-2010). She held Visiting Scholar appointments at SUPELEC, Universite’ Paris Sud, Princeton University and University of Southern California. Dr. Petropulu’s research interests span the area of statistical signal processing, wireless communications, signal processing in networking, physical layer security, and radar signal processing. Her research has been funded by various government industry sponsors including the National Science Foundation (NSF), the Office of Naval research, the US Army, the National Institute of Health, the Whitaker Foundation, Lockheed Martin and Raytheon. Dr. Petropulu is Fellow of IEEE and the American Association for the Advancement of Science (AAAS), and recipient of the 1995 Presidential Faculty Fellow Award given by NSF and the White House. She is 2022 President of the IEEE Signal Processing Society (SPS) and 2020 President-Elect of IEEE SPS. She has served as Editor-in-Chief of the IEEE Transactions on Signal Processing (2009-2011) and IEEE Signal Processing Society Vice President-Conferences (2006-2008). She was General Chair of 2020 and 2021 IEEE SPS PROGRESS Workshops, General Co-Chair of the 2018 IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Kalamata Greece, and Genera Chair of the 2005 International Conference on Acoustics Speech and Signal Processing (ICASSP-05), Philadelphia PA. She was Distinguished Lecturer for the Signal Processing Society for 2017-2018, and is currently Distinguished Lecturer for the IEEE Aerospace & Electronics Systems Society. She is recipient of the 2012 IEEE Signal Processing Society Meritorious Service Award, and co-recipient of the 2005 IEEE Signal Processing Magazine Best Paper Award, the 2020 IEEE Signal Processing Society Young Author Best Paper Award (B. Li), the 2021 IEEE Signal Processing Society Young Author Best Paper Award (F. Liu), and the 2021 Barry Carlton Best Paper Award by IEEE Aerospace and Electronic Systems Society.

 

Gridless Channel Estimation for Hybrid MIMO OFDM Systems in the Millimeter Wave Band via R-D Unitary Tensor-ESPRIT in DFT Beamspace
Martin Haardt Ilmenau University of Technology

Abstract: In this talk, we present a gridless channel estimation scheme for MIMO OFDM systems in the millimeter wave (mmWave) band that is based on R-D Unitary Tensor-ESPRIT in DFT beamspace. Compared to conventional ESPRIT based algorithms in element space, the beamspace approach can be applied to MIMO systems with hybrid architectures. Moreover, the proposed scheme significantly reduces the training overhead for communication systems operating in the mmWave band. The proposed procedure involves coarse and fine estimation steps. During the coarse estimation step, Unitary Tensor-ESPRIT in element space may be applied to the array with a reduced size aperture to obtain initial information about the directions of arrival, the directions of departure, and the propagation delays of the dominant multipath components. Based on these estimates, a more accurate estimation of the angular profiles, propagation delays, and channel gains is performed in a second step by applying 3-D Unitary Tensor-ESPRIT in DFT beamspace in the spatial domains combined with the element space version in the frequency domain. We explain how to combine the received signals from different spatial sectors of interest and how to perform joint processing. The simulation results confirm the tensor gain of the proposed procedure in addition to the improved channel estimation accuracy. 

Martin Haardt has been a Full Professor in the Department of Electrical Engineering and Information Technology and Head of the Communications Research Laboratory at Ilmenau University of Technology, Germany, since 2001. After studying electrical engineering at the Ruhr-University Bochum, Germany, and at Purdue University, USA, he received his Diplom-Ingenieur (M.S.) degree from the Ruhr-University Bochum in 1991 and his Doktor-Ingenieur (Ph.D.) degree from Munich University of Technology in 1996. In 1997 he joint Siemens Mobile Networks in Munich, Germany, where he was responsible for strategic research for third generation mobile radio systems. From 1998 to 2001 he was the Director for International Projects and University Cooperations in the mobile infrastructure business of Siemens in Munich, where his work focused on mobile communications beyond the third generation. During his time at Siemens, he also taught in the international Master of Science in Communications Engineering program at Munich University of Technology.  In 2018, Martin Haardt has been named an IEEE Fellow “for contributions to multi-user MIMO communications and tensor-based signal processing.” He has received the 2009 Best Paper Award from the IEEE Signal Processing Society, the Vodafone (formerly Mannesmann Mobilfunk) Innovations-Award for outstanding research in mobile communications, the ITG best paper award from the Association of Electrical Engineering, Electronics, and Information Technology (VDE), and the Rohde & Schwarz Outstanding Dissertation Award.  In the fall of 2006 and the fall of 2007, he was a visiting professor at the University of Nice in Sophia-Antipolis, France, and at the University of York, UK, respectively. From 2012 to 2017, he also served as an Honorary Visiting Professor in the Department of Electronics at the University of York, UK, and in 2019 as an Invited Professor at the Université de Lorraine in Nancy, France.  His research interests include wireless communications, array signal processing, high-resolution parameter estimation, as well as numerical linear and multi-linear algebra. Prof. Haardt has served as an Associate Editor for the IEEE Transactions on Signal Processing (2002-2006 and 2011-2015), the IEEE Signal Processing Letters (2006-2010), the Research Letters in Signal Processing (2007-2009), the Hindawi Journal of Electrical and Computer Engineering (since 2009), the EURASIP Signal Processing Journal (2011-2014), as a senior editor of the IEEE Journal of Selected Topics in Signal Processing (JSTSP, since 2019), and as a guest editor for the EURASIP Journal on Wireless Communications and Networking as well as the IEEE JSTSP.  From 2011 to 2019 he was an elected member of the Sensor Array and Multichannel (SAM) technical committee of the IEEE Signal Processing Society, where he served as the Vice Chair (2015 – 2016), Chair (2017 – 2018), and Past Chair (2019). Since 2020, he has been an elected member of the Signal Processing Theory and Methods (SPTM) technical committee of the IEEE Signal Processing Society. Moreover, he has served as the technical co-chair of PIMRC 2005 in Berlin, Germany, ISWCS 2010 in York, UK, the European Wireless 2014 in Barcelona, Spain, as well as the Asilomar Conference on Signals, Systems, and Computers 2018, USA, and as the general co-chair of WSA 2013 in Stuttgart, Germany, ISWCS 2013 in Ilmenau, Germany, CAMSAP 2013 in Saint Martin, French Antilles, WSA 2015 in Ilmenau, SAM 2016 in Rio de Janeiro, Brazil, CAMSAP 2017 in Curacao, Dutch Antilles, SAM 2020 in Hangzhou, China, and the Asilomar Conference on Signals, Systems, and Computers 2021, USA.