Title: Integrated Sensing and Communication Systems for 6G:

Topics on Waveform Design, Reinforcement Learning and Signal Processing

Abstract: Integrated Sensing and Communications Systems (ISAC) perform radio frequency sensing and transfer wireless data jointly. They operate in a shared and congested spectrum. We are considering ISAC systems that cooperate or are co-designed for mutual benefits. Co-designed systems may share HW and antenna resources as well as awareness about the state of the radio spectrum. The ISAC systems have a number of operational parameters that can be adjusted either by using structured optimization or machine learning. We focus on multicarrier waveforms used by most current and emerging wireless communication systems. Similarly, multicarrier waveforms have been employed for radar purposes. We will present waveform optimization, machine learning, interference management and signal processing methods for co-designed ISAC systems that share spectrum awareness. Model-based reinforcement learning approach is taken to exploit the rich structural knowledge of man-made communication and sensing systems and propagation effects to choose optimal actions. Optimization methods impose constraints that ensure minimum desired performance levels for other sub-systems. The developed OFDM radar signal processing algorithms in ISAC can take advantage of nonidealities such as carrier offsets 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 simulation and analytical results.

Bio:

Visa Koivunen (IEEE Fellow, EURASIP Fellow) received his D.Sc. (EE) degree with honors from the Univ of Oulu, Dept. of Electrical Engineering. He was a visiting researcher at the Univ of Pennsylvania, Philadelphia, USA, 1991-1995 and adjunct full professor in 2003-2006. Since 1999 he has been a full Professor of Signal Processing at Aalto University (formerly HUT), Finland. He received the Academy professor position in 2010 and Aalto Distinguished professor in 2020. During his sabbatical terms in 2006-2007 and 2013-2014 he was a visiting faculty at Princeton University and has had many mini-sabbaticals there over the years. He has also been a Visiting Fellow at Nokia Research (2006-2012). On his sabbatical term in 2022-23, he is visiting professor at EPFL, Lausanne, Switzerland.

Dr. Koivunen's research interests include statistical signal processing, wireless comms, radar, multisensor systems and machine learning. He has published more than 460 papers in international scientific conferences and journals and holds 5 patents. 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 has served in editorial boards for Proceedings of the IEEE, IEEE SP Letters, IEEE TR on SP, and IEEE SP Magazine and a variety of IEEE boards, panels and committees. 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.