A Novel Extrapolation Technique to Accelerate WMMSE

Abstract

Precoding design is essential for massive multi-user multiple-input multiple-output (MU-MIMO) systems, which aims at maximizing the weighted sum-rate (WSR). This problem is known to be NP-hard, and iterative algorithms are typically used to approximately solve it. The weighted minimum mean-squared error (WMMSE) algorithm is a popular solver for WSR maximization, which efficiently finds a local maxima of WSR. In this work, we introduce a novel extrapolation technique to further accelerate WMMSE. This technique is inspired by the momentum technique in convex optimization, and can be interpreted as an accelerated second-order method. The merits of the proposed extrapolation technique are (i) lightweight, as it almost does not increase the iteration complexity, (ii) generic, since it works in various settings such as the sum power constraint or per-antenna power constraint cases and coordinated multi-point joint transmission networks, and (iii) effective, that our simulation results show it significantly accelerates the convergence of WMMSE in the high channel correlation regime.