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Integrated Sensing and Communication Systems for 6G: Topics on Waveform Design, Reinforcement Learning and Signal Processing

E389 / News / Integrated Sensing and Communication Systems for 6G: Topics on Waveform Design, Reinforcement Learning and Signal Processing
24. November 2023
It is a pleasure to cordially invite you on 24. Nov. 2023, 09:00 a.m., to a talk on integrated sensing and communication to be given by Prof. Visa Koivunen (http://users.spa.aalto.fi/visa/) from Aalto University, a leading expert in the field. Further details can be found below.

Speaker: Prof. Visa Koivunen (Aalto University)
Place: seminar room 389 (CG0118)

Abstract: Integrated Sensing and Communications Systems (ISAC) perform radio frequency sensing and transfer wireless data jointly. They operate in a shared and congested spectrum. ISAC systems will be an integral part of emerging 6G wireless systems. 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. Both structured optimization and reinforcement learning methods are developed to exploit the rich structural knowledge of man-made communication and sensing systems while learning from data. Optimization and learning impose constraints that ensure minimum desired performance levels for other sub-systems. We have also developed OFDM radar signal processing algorithms for ISAC that can take advantage of nonidealities such as carrier offsets and phase noise, 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.

Biography: 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. He has also been a Visiting Fellow at Nokia Research (2006-2012). Since 2010 he has spent mini-sabbaticals at Princeton University each year. On his sabbatical term in 2022-23, he was visiting professor at EPFL, Lausanne, Switzerland. Dr. Koivunen’s research interest include statistical signal processing, wireless comms, radar, multisensor systems and machine learning. He was awarded the IEEE SP Society best paper award for the year 2007 (with J. Eriksson) and 2017 (w Zoubir, Muma and Chakhchouk) and received multiple best conference paper awards. He has served on the editorial board for the Proceedings of the IEEE, IEEE SP Letters, IEEE TR on SP, and IEEE SP Magazine. He has served in IEEE Fourier Award, Kilby medal and Fellow Evaluation committees for IEEE SPS and AES and SPS Award Board, AES radar systems panel, and NATO radar panels. 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.

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