KEYNOTE SPEAKERS

Discrete signal detection using compressed sensing technique
Prof. Dr. Kazunori Hayashi
Kyoto University, Japan

Abstract
The unknown vector reconstruction from its linear measurements is one of typical problems in communications systems, such as channel equalization, channel estimation, MIMO (multi-input multi-output) signal detection, and IoT (internet-of-things) signal detection. In conventional approaches, the number of observations in linear measurements is assumed to be greater than or equal to that of unknown vector elements. For example, in MIMO signal detection problem, the number of receiving antennas should be greater than or equal to that of transmit streams. In order to improve the spectral efficiency, it is preferable to cope with the scenario where the number of linear measurements is possibly less than that of dimension of the unknown vector, namely, underdetermined linear measurements. This talk explains fundamental ideas to recover an unknown discrete and/or sparse vector from underdetermined linear measurements by using compressed sensing technique, and show some examples of applications in communications systems.

Biography
Kazunori Hayashi is currently a Professor at the Center for Innovative Research and Education in Data Science / Graduate School of Informatics, Kyoto University. He received the B.E., M.E., and Ph.D. degrees in communication engineering from Osaka University,Osaka, Japan, in 1997, 1999, and 2002, respectively. He was an Assistant Professor from 2002 to 2007, an Associate Professor from 2007 to 2017 at the Graduate School of Informatics, Kyoto University, and a Professor from 2017 to 2020 at the Graduate School of Engineering, Osaka City University. His research interests include statistical signal processing for communications systems. He received the ICF Research Award from the KDDI Foundation in 2008, the IEEE Globecom Best Paper Award in 2009, the IEICE Communications Society Best Paper Award in 2010, the WPMC’11 Best Paper Award, the Telecommunications Advancement Foundation Award in 2012, the IEICE Communications Society Best Tutorial Paper Award in 2013, APSIPA ASC Best Special Session Paper Nomination Award in 2019, and APSIPA ASC Best Paper Award in 2021. He is a member of IEEE, APSIPA, IEICE, and ISCIE.