Wei Yu

Title: Active Learning for Communications and Sensing Speaker: Wei Yu, University of Toronto 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 a recurrent neural networks based on a long short-term memory architecture 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 and for configuring the reflective coefficients of reconfigurable intelligent surface in a sequential manner for both localization and object tracking. Biography Wei Yu is a Professor in the Electrical and Computer Engineering Department at the University of Toronto, where he holds a Canada Research Chair in Information Theory and Wireless Communications. He received a Ph.D. degree in Electrical Engineering from Stanford University. He is a Fellow of the IEEE and a Fellow of the Canadian Academy of Engineering. He received the Steacie Memorial Fellowship in 2015, 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.