Globally Optimal Resource Allocation for Achieving Maximum Weighted Sum Rate

We establish a general optimization framework for joint resource allocation and interference mitigation. By utilizing axiomatic interference functions, our problem formulation is very general and includes many problems as special cases. We consider the sum rate maximization problem, which is known to be NP hard. It is shown that due to the structural model of the interference function, the joint optimization of powers and adaptive receive strategies ends up with the optimization solely with respect to powers. This facilitates a reformulation of the problem under consideration as a problem of difference of convex functions (DC). Based on this DC representation, we employ a prismatic branch and bound algorithm to find a global optimum.