Power Amplifier-aware Power Allocation for Noise-limited and Distortion-limited Regimes

TL;DR

This paper introduces a power allocation method that accounts for power amplifier nonlinearity, enabling operation in regimes with significant distortion and improving capacity over traditional water-filling strategies.

Contribution

It integrates PA nonlinearity into power allocation, deriving a new regime threshold and proposing an optimization algorithm for better performance in saturation.

Findings

Amplifier-aware power allocation outperforms water-filling in saturation regimes.

A closed-form threshold distinguishes noise-limited and distortion-limited regimes.

Numerical results show capacity gains in the saturation regime.

Abstract

The conventional power allocation strategy via water-filling relies on the premise that the power amplifier (PA) operates sufficiently below saturation such that a linear RF chain model holds. This work integrates the PA nonlinearity directly into the power allocation formulation, thereby removing the linearity assumption altogether and enabling operation in regimes where distortion noise is non-negligible. Leveraging the Bussgang theorem, we establish a statistical linearization of the PA's hard-limiting model to characterize the trade-off between signal gain and power-dependent distortion. We propose a projected gradient descent algorithm that optimizes power allocation while identifying an optimal spatial back-off strategy. We also derive a closed-form thermal noise variance threshold that separates the noise-limited and distortion-limited operating regimes as a function of the distortion noise variance and the channel Frobenius norm. Numerical simulations validate that our amplifier-aware strategy provides significant capacity gains in the saturation regime compared to standard water-filling.