Distortion-Aware Linear Precoding for Massive MIMO Downlink Systems with Nonlinear Power Amplifiers

TL;DR

This paper proposes a new linear precoding framework for massive MIMO downlink systems that accounts for nonlinear power amplifier distortions, improving spectral and energy efficiency.

Contribution

It introduces distortion-aware precoding algorithms that optimize for sum rate and power consumption considering PA nonlinearities.

Findings

Significant spectral efficiency improvements over conventional precoding.

Enhanced energy efficiency through power minimization algorithms.

Effective distortion mitigation in multiuser massive MIMO systems.

Abstract

We introduce a framework for linear precoder design over a massive multiple-input multiple-output downlink system in the presence of nonlinear power amplifiers (PAs). By studying the spatial characteristics of the distortion, we demonstrate that conventional linear precoding techniques steer nonlinear distortions towards the users. We show that, by taking into account PA nonlinearity, one can design linear precoders that reduce, and in single-user scenarios, even completely remove the distortion transmitted in the direction of the users. This, however, is achieved at the price of a reduced array gain. To address this issue, we present precoder optimization algorithms that simultaneously take into account the effects of array gain, distortion, multiuser interference, and receiver noise. Specifically, we derive an expression for the achievable sum rate and propose an iterative algorithm that attempts to find the precoding matrix which maximizes this expression. Moreover, using a model for PA power consumption, we propose an algorithm that attempts to find the precoding matrix that minimizes the consumed power for a given minimum achievable sum rate. Our numerical results demonstrate that the proposed distortion-aware precoding techniques provide significant improvements in spectral and energy efficiency compared to conventional linear precoders.