A Novel Fractional Programming Approach for Two Typical Power Allocation Optimization Problems in Multi-User Massive MIMO Systems

In multi-user millimeter wave (mmWave) communications, massive multiple-input multiple-output (MIMO) systems can achieve high gain and spectral efficiency significantly. In this paper, we focus on the maximization of the weighted sum rate and the global optimization of the max-min fairness problem, which are not only important but also very hard to find the global optimal solutions due to their nonconvexity property. Some previous works on the power allocation for maximization of the weighted sum rate usually proposed methods that either have high complexity or achieve sub-optimal performance. And there are few previously developed algorithms for finding the global optimal solution of the max-min fairness optimization problem. Based on a quadratic transform (QT) technique, which is a novel fractional programming (FP) approach, we introduce efficient iterative algorithms with low complexity to find optimal solutions of the two typical and difficult power allocation problems in wireless communications. Simulation evaluations demonstrate that our proposed algorithms are able to provide the optimal solutions and outperform previous methods in both performance and computational complexity.