Capacity, coding and optimization for network information theory

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Network information theory is a fundamental theory of communication in a multiuser environment. This past decade has witnessed a tremendous surge of research interests in this area, driven, in part, by insatiable demands for high-speed wireless service and Internet access. It has been increasingly recognized that not only are the capacity theorems of network information theory ideally suited in providing a theoretical framework for the physical-layer design of communication systems, they also play an instrumental role in providing practical engineering insights for networking and content-distribution protocols at the network and application layers. The proposed research program aims to gain fundamental insights into long-standing capacity problems in network information theory by focusing on the following areas. First, the proposed research will investigate capacity limits and develop practical coding and modulation strategies for wireless cooperative communications. The proposed research will take advantage of recent advances in error-correcting codes and in statistical physics to develop capacity-approaching strategies for multiuser channels, such as the broadcast channel and the relay channel. Second, the proposed research will address the computation of capacity limits in network information theory using convex optimization techniques. This is especially important in practical wireless multi-antenna communication scenarios where many degrees of freedom in transmitter design are available. Finally, novel multiuser channel models inspired by networking problems will be formulated, and insights gained from the study of capacity and coding for these channels will be used to address the design of practical networking protocols. Together, the overall research program aims to tackle theoretical issues in multiuser communication, and to gain fresh insights into the nature of information flow in a network.