An information-theoretic perspective on interference management


Atkinson Hall, Room 4004


For high data rates and massive connectivity, next-generation cellular networks are expected to deploy many small base stations. While such dense deployment provides the benefit of bringing radio closer to end users, it also increases the amount of interference from neighboring cells. Consequently, efficient and effective management of interference is expected to become one of the main challenges for high-spectral-efficiency, low-power, broad-coverage wireless communications.

In this talk, we introduce two competing paradigms of interference management and discuss recent developments in network information theory under these paradigms. In the first "distributed network" paradigm, the network consists of autonomous cells with minimal cooperation. We explore advanced channel coding techniques for the corresponding mathematical model of the "interference channel," focusing mainly on the sliding-window superposition coding scheme that achieves the performance of simultaneous decoding through point-to-point channel codes and low-complexity decoding. In the second "centralized network" paradigm, the network is a group of neighboring cells connected via backhaul links. For uplink and downlink communications over this "two-hop relay network," we develop dual coding schemes -- noisy network coding and distributed decode-forward -- that achieve capacity universally within a few bits per degree of freedom.


Young-Han Kim received his B.S. degree with honors in electrical engineering from Seoul National University, Korea, in 1996 and his M.S. degrees in electrical engineering and in statistics, and his Ph.D. degree in electrical engineering from Stanford University in 2001, 2006, and 2006, respectively. In 2006, he joined the University of California, San Diego, where he is currently an Associate Professor in the Department of Electrical and Computer Engineering. His research interests are in information theory, communication engineering, and data science. He coauthored the book Network Information Theory (Cambridge Press 2011). He is a recipient of the 2008 NSF Faculty Early Career Development (CAREER) Award, the 2009 US-Israel Binational Science Foundation Bergmann Memorial Award, the 2012 IEEE Information Theory Paper Award, and the 2015 IEEE Information Theory Society James L. Massey Research and Teaching Award for Young Scholars. He served as an Associate Editor of the IEEE Transactions on Information Theory and a Distinguished Lecturer for the IEEE Information Theory Society. He is a Fellow of the IEEE.