6G Research Visions Webinar Series:

Localization and Sensing – Technologies, Opportunities and Challenges

Wednesday 18 November 2020 at 5:00-6:30 PM (Helsinki, UTC/GMT +02:00, CET +01:00)

About the Event

As part of the 6G Research Visions Webinar Series, this webinar will explore future localization and sensing opportunities for beyond-5G wireless communication systems by identifying key technology enablers and discussing their underlying challenges, implementation issues, and identifying potential solutions. In addition, we present exciting new opportunities for localization and sensing applications, which will disrupt traditional design principles and revolutionize the way we live, interact with our environment, and do business.

The webinar is moderated by Dr. Carlos H. M. de Lima who led the Expert Group that compiled the 6G Whitepaper on Localization and Sensing.

Talks by Expert Group representatives:

6G Technology challenges & system-level Opportunities through THz spectrum adoption by Barend Van Liempd, IMEC, Belgium

Intelligent surface-assisted communications, localization, and sensing by Hadi Sarieddeen, King Abdullah University of Science and Technology (KAUST), Saudi Arabia

Beamspace for localization and sensing by Yang Miao, University of Twente, Netherlands

Role of machine learning in localization and sensing by Jaakko Suutala, University of Oulu, Finland

Sensing and communication convergence by Henk Wymeersch and Tommy Svensson, Chalmers University of Technology, Sweden

Active Radar Sensing Using Joint Communications and RF Sensing by André Noll Barreto, Barkhausen Institut, Germany

After the talks, a minimum of 30 minutes is reserved for open discussion with the distinguished presenters. A recorded video of the webinar will be openly available after the event.

Carlos H. M. de Lima received the B.Sc. and M.Sc. in Electrical Engineering from the Federal University of Ceará (UFC), Brazil in 2002 and 2004, respectively. In 2013, he received the Dr.Sc (Tech) degree in communications engineering from the University of Oulu, Finland. From 2000 to 2005, he worked as research scientist in the Wireless Telecommunication Research Group (GTEL), Brazil. In 2006, he worked at the Nokia Institute of Technology (INdT), Brazil. From 2014 to 2018, he worked as an assistant professor at the São Paulo State University (UNESP), Brazil. Currently, he is a senior research fellow with the Centre for Wireless Communications (CWC), University of Oulu, Finland. He contributed to the projects FP7 EUWB, FP7 BeFemto, FP7 Duplo and H2020 SAT5G. His research interests are statistical signal processing, information fusion and analytics and probabilistic programming.

Barend Van Liempd received the B.Sc. and M.Sc. degree in electrical engineering from the Eindhoven University of Technology, Eindhoven, The Netherlands, in 2009 and 2011, respectively, and the Ph.D. degree from Vrije Universiteit Brussel, Brussels, Belgium, in 2017, in collaboration with IMEC, Leuven, Belgium. His Ph.D. dissertation concerned tunable, highly integrated RF front-end circuits and modules in SOI CMOS. In 2011, he joined IMEC, where he was an Research and Development Engineer on multi-standard transceivers, until 2014, and became a Ph.D. Researcher and a Senior Researcher in 2017. Recently, he was appointed Program Manager Radar, and now leads IMEC’s radar R\&D activities. He has authored or co-authored over 30 papers, patents, and patent applications. His research interests are analog, RF, and millimeter-wave circuits for wireless and sensing applications. Dr. van Liempd was a recipient of the 2015 NXP Prize at the European Microwave IC conference.

Hadi Sarieddeen received his B.E. degree in computer and communications engineering from Notre Dame University-Louaize, Lebanon, in 2013 (summa cum laude, first in graduating class), and his Ph.D. degree in electrical and computer engineering from the American University of Beirut (AUB), Lebanon, in 2018. He is currently a postdoctoral research fellow at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. His research interests are in the area of signal processing for wireless communications, with an emphasis on signal processing for converged terahertz communications and sensing.

Yang Miao received her M.Sc. and PhD degrees from the Radio Propagation Laboratory, Mobile Radio Communication Group, Tokyo Institute of Technology, Japan, in Sep. 2012 and Sep. 2015, respectively. From 2015 to 2018, she was a Postdoctoral Researcher with Prof. Claude Oestges, Universite Catholique de Louvain, and with IMEC-WAVES, Ghent University, Belgium. From 2018 to 2019, she was working under the Shenzhen Peacock Talent Program, first as a Senior Engineer in Jaguar Radio Tech., and then as a Research Assistant Professor in the Southern University of Science and Technology, China. From Aug. 2019, she becomes an Assistant Professor in the Radio System, Department of Electrical Engineering, University of Twente, the Netherlands. She was a visiting researcher in Aalto University, Chalmers University of Technology, Cambodia Institute of Technology, Katholieke University of Leuven, and Ranplan Wireless UK. Her research interests are mainly in the interactions between antenna arrays and radio propagation environment including the presence of human. Specific topics include the passive and active radio channel measurement, antenna de-embedding, channel characterization and modeling, optimization of multiantenna array configuration and massive MIMO topology, channel emulation in multi-probe anechoic chamber for over-the-air testing, room electromagnetics and reverberation, orthogonal modes and multi-mode channel, deterministic ray tracer and propagation graph, diffuse scattering, radio channel assisted passive human detection, localization and posture identification.

Jaakko Suutala is an assistant professor of artificial intelligence in Biomimetics and Intelligent Systems group in the Faculty of Information Technology and Electrical Engineering at University of Oulu, Finland. He received the M.Sc. degree in information engineering in 2004, and the D.Sc. degree in computer science and engineering in 2012, both from University of Oulu. In 2007 he was a visiting researcher at Tokyo University of Agriculture and Technology, Japan. His research interests are machine learning, statistical signal processing, and data science. He is a co-founder and technical advisor of IndoorAtlas Ltd., indoor localization spin-off company from University Oulu.

Henk Wymeersch obtained the Ph.D. degree in Electrical Engineering/Applied Sciences in 2005 from Ghent University, Belgium. He is currently a Professor of 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. Prior to joining Chalmers, he was a postdoctoral researcher from 2005 until 2009 with the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology. Prof. Wymeersch served as Associate Editor for IEEE Communication Letters (2009-2013), IEEE Transactions on Wireless Communications (since 2013), and IEEE Transactions on Communications (2016-2018). During 2019-2021, he is a IEEE Distinguished Lecturer with the Vehicular Technology Society. His current research interests include the convergence of communication and sensing, in a 5G and Beyond 5G context.

Tommy Svensson is full Professor in Communication Systems at Chalmers University of Technology in Gothenburg, Sweden, leading Wireless Systems research on air interface and networking technologies for access, backhaul/ fronthaul in 5G and Beyond/ 6G mobile communications. He received a Ph.D. in Information theory from Chalmers in 2003, has worked at Ericsson AB with core networks, radio access networks, and microwave transmission products, and has been deeply involved in European research towards 4G and 5G system concepts. His research interests include design and analysis of physical layer algorithms, multiple access, resource allocation, cooperative MIMO systems, C-V2X, and satellite networks. He has co-authored 5 books, 89 journal papers, 127 conference papers and 53 public EU projects deliverables. He has been editor of IEEE TWC, WCL, and is founding editorial board member and editor of IEEE JSAC Series on
Machine Learning in Communications and Networks.

André Noll Barreto (Senior Member, IEEE) received the M.Sc. degree from Catholic University (PUC-Rio), Rio de Janeiro, Brazil, in 1996, and the Ph.D. degree from Technische Universität Dresden, Germany, in 2001, both in Electrical Engineering. After several positions in academia and industry in Switzerland (IBM Research) and Brazil (Claro, Nokia Technology Institute/INDT, Universidade de Brasília, Ektrum), he joined Barkhausen Institut, Dresden, Germany, in 2018, where he is leading the Wireless Connectivity research group. He is currently investigating wireless communications for a reliable, resilient, and secure Internet of Things, and is particularly interested in the topic of joint communications and sensing

Organizers

The webinar series is organized by the Finnish 6G Flagship program and representatives of the 6G White Paper Expert Groups. For more information please contact us via 6gflagship@oulu.fi.

Highlights of the 6G White Paper on Localization and Sensing

We discuss the 6G convergent communication, localization and sensing systems by addressing the following indispensable aspects: i) we first identified the most promising technologies which will most likely pave the way towards the next generation of wireless communication systems, then ii) based on the desired features of the upcoming 6G networks and the opportunities created by the enabling technologies, we discuss interesting new applications which will impact the way we live, interact with our environment, and do business, finally iii) we discuss challenges and identify future directions to realize truly intelligent 6G wireless systems that will not only provide ubiquitous communication but also empower high accuracy localization and high-resolution sensing services.