Informationally Efficient Multi-User Communication

The rapid increase in the demand for data rate over wired and wireless communication networks has led to a rethinking of the traditional network architecture and design principles. In fact, communication systems are inherently informationally decentralized competitive environments, where multiple devices executing a variety of applications and services need to locally adapt their transmission strategies based on their available information and compete for scarce networking resources. The concepts and techniques that have dominated multi-user communication research in recent years are not well suited for these informationally decentralized environments. Specifically, most existing research has focused on two extreme multi-user interaction scenarios, the complete information scenario with a common system-wide objective (e.g. Pareto optimality) and the private information scenario with conflicting objectives (e.g. Nash equilibrium (NE)).;The objective of this dissertation is to characterize users' optimal strategies to improve their performance subject to varying degrees of informational constraints. We mainly focus on fully distributed solutions without any real-time information exchange between different users. In particular, we investigate three key problems in information-constrained multi-user communication systems. First, when will a distributed algorithm (e.g. best response dynamics) converge to a NE? And how fast? Second, if information is constrained and no real-time information exchange between users is allowed, how to improve an inefficient NE without message passing? Last, assuming no real-time information exchange between users, can we still achieve Pareto optimality? We propose and analyze two new classes of games named additively coupled sum constrained games and linearly coupled games, in which we individually address these three questions. In particular, we provide sufficient conditions under which a unique NE exists and best response dynamics linearly converges to the NE. We also provide conjectural equilibrium based solutions that can substantially improve the performance of inefficient NE and fully recover Pareto optimality without any real-time information exchange between users. The proposed game models apply to a variety of realistic applications in multi-user communication systems, including multi-channel power control, flow control, and wireless random access.