Wireless Transceivers based on Amortized Optimization

Abstract: In many real-world optimization applications, instances of the same type of optimization problem are repeatedly solved regularly, with the same problem structure and differing mainly in their data. In principle, there exists a mapping from the problem data space to the space of the optimum solutions. In diverse scientific and commercial settings, one may be willing to invest in upfront, offline computation and learning of such a mapping to speed up real-time decision-making and improve its quality. We explore the potential of neural networks to learn the solutions of a target family of continuous or combinatorial optimization problems. For the trained network to attain the optimum and to speed up the training process, we propose to take a principled approach based on the notion that learning is more efficient when simple tasks are learned before more complex ones and investigate various curriculum learning techniques. We apply the proposed framework to several transceiver design problems in next-generation wireless systems, such as transmitter beamforming and receiver demodulation.

Bio: Xiaodong Wang received the Ph.D degree in Electrical Engineering from Princeton University. He is a Professor of Electrical Engineering at Columbia University in New York. Dr. Wang's current research interests fall in the general areas of computing, signal processing and communications, and has published extensively in these areas. Among his publications is a book entitled "Wireless Communication Systems: Advanced Techniques for Signal Reception". His current research interests include wireless communications, statistical signal processing, machine learning and quantum information processing. Dr. Wang received the 1999 NSF CAREER Award, the 2001 IEEE Communications Society and Information Theory Society Joint Paper Award, and the 2011 IEEE Communication Society Award for Outstanding Paper on New Communication Topics. He has served as an Associate Editor for the IEEE Transactions on Communications, the IEEE Transactions on Wireless Communications, the IEEE Transactions on Signal Processing, and the IEEE Transactions on Information Theory. He is a Fellow of the IEEE and listed as an ISI Highly-cited Author.