Power Allocation Algorithms for Massive MIMO Systems with Multi-Antenna Users

TL;DR

This paper addresses power allocation in massive MIMO systems with multi-antenna users, simplifying spectral efficiency analysis and proposing low-complexity algorithms that outperform equal power allocation under practical constraints.

Contribution

It introduces tractable spectral efficiency expressions and novel Intersection Methods for power allocation, improving performance under per-antenna power constraints.

Findings

Equal power allocation is optimal under total power constraint.

Intersection Methods enhance spectral efficiency with low complexity.

Proposed methods outperform traditional solutions in simulations.

Abstract

Modern 5G wireless cellular networks use massive multiple-input multiple-output (MIMO) technology. This concept entails using an antenna array at a base station to concurrently service many mobile devices that have several antennas on their side. In this field, a significant role is played by the precoding (beamforming) problem. During downlink, an important part of precoding is the power allocation problem that distributes power between transmitted symbols. In this paper, we consider the power allocation problem for a class of precodings that asymptotically work as regularized zero-forcing. Under some realistic assumptions, we simplify the spectral efficiency functional and obtain tractable expressions for it. We prove that equal power allocation provides optimum for the simplified functional with total power constraint (TPC). We propose low-complexity Intersection Methods (IM) that improve equal power allocation in the case of per-antenna power constraints (PAPC). On simulations using Quadriga, the proposed IM method in combination with widely-studied Water Filling (WF) shows a significant gain in spectral efficiency while using a similar computing time as the reference Equal Power (EP) solution.