Information theory aims to characterize the fundamental limits of storing, processing, and transmission of information in communication networks. As an example, to identify one of N distinct objects, log(N) bits of information are required. Moreover, the maximum rate of information transmission through a noisy channel is approximately the logarithm of the signal-to-noise ratio. In this talk, we explore several unusual scenarios where information theoretical analyses yield surprising results. We ask the following questions: 1) Is it possible to transmit information through a noisy channel at a positive rate using only infinitesimal amount of transmit power? 2) For transmitting independent messages to a subset of K active devices among a large pool of N devices, is it possible to avoid using headers of size log(N) bits to identify the intended recipient of each message? The answers to both questions are surprisingly yes! We discuss the implications of these results to cooperative communications and to massive random access in wireless networking.
Wei Yu received the B.A.Sc. degree in computer engineering and mathematics from the University of Waterloo, Canada, and the M.S. and Ph.D. degrees in electrical engineering from Stanford University. He is currently a Professor and Canada Research Chair in Information Theory and Wireless Communications in the Electrical and Computer Engineering Department at the University of Toronto in Canada. Prof. Yu is a Fellow of IEEE and a Fellow of the Canadian Academy of Engineering. He was the recipient of 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 and Information Theory Society Joint Paper Award in 2024. Prof. Yu is a Clarivate Highly Cited Researcher. He served as the President of the IEEE Information Theory Society in 2021.