Toward a Many-User Information Theory: Initial Results

Professor Dongning Guo
Professor, Northwestern University
Given on: Feb. 6th, 2014


Classical multiuser information theory studies the fundamental limits of models with a fixed (often small) number of users as the coding blocklength goes to infinity. In this talk, we introduce a new many-user paradigm, where the number of users and the blocklength simultaneously tend to infinity. This paradigm is motivated by emerging systems whose massive number of users is comparable or far exceeds the blocklength, such as in machine-to-machine communication systems and sensor networks. The focus of the talk is the Gaussian many-access channel, which consists of a single receiver and many transmitters with fixed power, where all or a subset of users may transmit in a given block and need to be identified. The conventional notion of capacity in bits per channel use is ill-suited for the task, as Cover and Thomas recognized that the rate per sender vanishes. A new notion of capacity is introduced and characterized for the Gaussian many-access channel. The capacity can be achieved by first detecting the set of active users and then decoding their messages. Also discussed are results on many-broadcast channels and our outlook on a general many-user information theory.


Dongning Guo joined the faculty of Northwestern University, Evanston, IL, in 2004, where he is currently an Associate Professor in the Department of Electrical Engineering and Computer Science. He received the B.Eng. degree from the University of Science & Technology of China, the M.Eng. degree from the National University of Singapore, and the M.A. and Ph.D. degrees from Princeton University. He has been an Associate Editor of the IEEE Transactions on Information Theory, an Editor of Foundations and Trends in Communications and Information Theory, and a Guest Editor for the IEEE Journal on Selected Areas in Communications. He was a co-recipient of the IEEE Marconi Prize Paper Award in Wireless Communications in 2010 and a recipient of the NSF CAREER Award. His research interests are in information theory, communications, and networking.