Distributed dynamic pricing for MIMO interfering multiuser systems: A unified approach

Wireless networks are composed of many users that usually have conflicting objectives and generate interference to each other. The system design is typically formulated as the optimization of the weighted sum of the users' utility functions. In an attempt to obtain distributed algorithms in the case this sum is nonconvex, researchers have proposed pricing mechanisms which however are based on heuristics and valid only for a restricted class of problems. In this paper we propose a general framework for the distributed optimization of the nonconvex sum-utility function. Our main contributions are: i) the derivation for the first time of a general dynamic pricing mechanism, ii) a framework that can be easily particularized to well-known applications, giving rise to very efficient practical algorithms that outperform existing methods; and iii) the solution to the currently open problem of social optimization for MIMO multiuser systems.