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.