Decentralized Sum Rate Maximization With QoS Constraints for Interfering Broadcast Channel Via Successive Convex Approximation

Weighted sum rate maximization (WSRMax) with user specific quality-of-service (QoS) constraints and general convex transmit power constraints is considered in multi-cell multi-user multiple-input multiple-output system. The particular focus in the proposed joint transmitter-receiver design is on tractability in terms of implementation and moderately fast changing/time correlated channel conditions. The non-convex transmit precoder design problem is formulated as a difference of convex functions program, for which a locally optimal solution is achieved by successive convex approximation (SCA). To achieve practically realizable designs, two decentralized approaches with low signaling overhead are proposed. Primal decomposition based solution provides better compliance of the provided QoS constraints in slowly fading channel conditions. On the other hand, solution based on Lagrangian relaxation of the coupling rate constraints is proposed for relaxed feasibility conditions and improved convergence properties. As a special case, an iterative solution via the Karush-Kuhn-Tucker conditions of the precoder design problem with per base station transmit power constraints is also proposed. Finally, we propose a heuristic extension of the SCA method, which is shown to significantly improve the rate of convergence while achieving comparable sum rate with recently published methods.