Optimality Conditions of Performance-Guaranteed Power Minimization in MIMO Networks: A Distributed Algorithm and Its Feasibility

Abstract

A distributed approach is proposed to the problem of signal-to-interference-plus-noise-ratio (SINR)-guaranteed power minimization (SGPM) for multicell multiuser (MCMU) multiple-input multiple-output (MIMO) systems. Unlike prior SGPM approaches, the proposed technique is based on solving necessary and sufficient optimality conditions, which are derived by decomposing the original problem into forward and backward (FB) subproblems, while ensuring the strong duality of each subproblem. The proposed distributed SGPM algorithm makes use of FB adaptation and Jacobi recursion, respectively, for iterative filter design and power allocation. A sufficient condition for the feasibility of the proposed distributed algorithm is analyzed, based on the matrix inverse-positive theory. Unlike the existing fully distributed FB filter update algorithms, the proposed approach guarantees target SINR performance as well as its convergence to a stationary point. Simulation results illustrate the enhanced power efficiency with the performance guarantees of the proposed method compared to the existing distributed techniques.