Monotonic Optimization Framework for the MISO IFC

Resource allocation and transmit optimization for the multiple-antenna Gaussian interference channel are important but difficult problems. Recently, there has been a large interest in algorithms that find operating points which are optimal in the sum-rate, proportional-fair, or minimax sense. Finding these points entails solving a nonlinear, non-convex optimization problem. In this paper, we develop an algorithm that solves these problems exactly, to within a prescribed level of accuracy and in a finite number of steps. The main idea is to rewrite the objective functions so that methods for monotonic optimization can be used. More precisely, we write each objective function as a difference between two functions which are strictly increasing over a normal constraint set. The so-obtained reformulated, equivalent problem can then be solved efficiently by using so-called polyblock optimization. Numerical examples illustrate the advantages of the proposed framework compared to an exhaustive grid search.©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Eduard A. Jorswieck and Erik G. Larsson, Monotonic Optimization Framework for the MISO IFC, 2009, Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 3633-3636.http://dx.doi.org/10.1109/ICASSP.2009.496041