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(August 11) Point-to-Point Codes for Interference Channels: A Journey toward High Performance at Low Complexity


Point-to-Point Codes for Interference Channels: A Journey toward High Performance at Low Complexity


2016/08/12 (Friday) 14:30


Young-Han Kim (University of California, San Diego)


Wooribyul Seminar Room (#2201)


For high data rates and massive connectivity, the 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, smart management of interference would become one of the key enabling technologies for high-spectral-efficiency, low-power, broad-coverage wireless communication.
In this talk, we discuss recent developments in channel coding techniques for interference channels, primarily focusing on the sliding-window superposition coding scheme. This coding scheme achieves the performance of simultaneous decoding with point-to-point channel codes and low-complexity decoding. Simulation results demonstrate that sliding-window superposition coding can sometimes double the performance of the conventional method of treating interference as noise, while still using the conventional off-the-shelf channel codes.
Joint work with Seok-Ki Ahn, Bernd Bandemer, Chiao-Yi Chen, Abbas El Gamal, Kwang Taik Kim, Hosung Park, Eren Sasoglu, and Lele Wang.


Young-Han Kim received his B.S. degree in Electrical Engineering from Seoul National University in 1996 and his Ph.D. degree in Electrical Engineering (M.S. degrees in Statistics and in Electrical Engineering) from Stanford University in 2006. Since then he has been a faculty member in the Department of Electrical and Computer Engineering at the University of California, San Diego, where he is currently an Associate Professor. Professor Kim is a recipient of the 2008 NSF CAREER Award, the 2009 US-Israel BSF Bergmann Memorial Award, the 2012 IEEE Information Theory Paper Award, and the 2015 IEEE James L. Massey Award. He is an IEEE Fellow. His research interests are information theory, communication engineering, and data science.