7th seminar - Active Sensing and Communications via Learning

Title: Active Sensing and Communications via Learning

Time: 10:30am on 2nd Jul. 2024    Location: 909B, EEE building

Abstract: Machine learning will play an important role in the optimization of future-generation physical-layer wireless communication systems for the following two reasons. First, traditional wireless communication design always relies on the channel model, but models are only an approximation to reality. In wireless environments where the modelling task is complex and the channels are costly to estimate, a learning-based approach can significantly outperform the traditional model-based approaches. Second, modern wireless communication design often involves optimization problems that are high-dimensional, nonconvex, and difficult to solve efficiently. By exploring the availability of training data, a neural network may be able to learn the solution of an optimization problem directly. This talk will focus on a data-driven approach for integrated sensing and communications system design. We show that recurrent neural networks can be trained to learn solutions to sequential active sensing problems effectively. The proposed learning-based approach can be used for designing active beamforming strategy for mmWave initial beam alignment, for actively tuning the reflective coefficients of reconfigurable intelligent surfaces in a sequential manner for both localization and object tracking, and for a two-sided beamforming problem for a massive MIMO systems with reciprocity based on ping-pong pilots.

Bio: Wei Yu is a Professor in Electrical and Computer Engineering at the University of Toronto, where he holds a Canada Research Chair in Information Theory and Wireless Communications. He received the B.A.Sc. degree in computer engineering and mathematics from the University of Waterloo, and the M.S. and Ph.D. degrees in electrical engineering from  Stanford University. Prof. Wei Yu is a Fellow of IEEE and a Fellow of the Canadian Academy of Engineering. He received the IEEE Communications Society and Information Theory Society Joint Paper Award in 2024, the IEEE Marconi Prize Paper Award in Wireless Communications in 2019, the IEEE Communications Society Award for Advances in Communication in 2019, the IEEE Signal Processing Society Best Paper Award in 2008, 2017 and 2021, and the IEEE Communications Society Best Tutorial Paper Award in 2015. Prof. Wei Yu served as the President of the IEEE Information Theory Society in 2021. He is a Clarivate highly cited researcher (2023).