Max-Min Multi-Cell Aware Precoding and Power Allocation for Downlink Massive MIMO Systems

TL;DR

This paper introduces a novel max-min multi-cell aware precoding and power allocation scheme for downlink massive MIMO systems, improving the minimum network rate by leveraging statistical CSI and random matrix theory.

Contribution

It proposes a new Max-Min MCA-RZF precoding scheme that accounts for channel estimation errors and pilot contamination, with deterministic equivalents derived for large systems.

Findings

Achieves higher minimum network rate compared to existing precoders.

Provides deterministic power allocation formulas based on statistical CSI.

Demonstrates significant performance improvements through numerical simulations.

Abstract

We propose a max-min multi-cell aware regularized zero-forcing (Max-Min MCA-RZF) precoding and power allocation scheme for downlink multi-cell massive multiple-input multiple-output (MIMO) systems. A general correlated channel model is considered, and the adopted channel state information (CSI) acquisition model includes the effects of estimation errors and pilot contamination. We use results from random matrix theory to derive deterministic equivalents for the proposed Max-Min power allocation in the large system limit which solely depend on statistical CSI, but not on individual channel realizations. Our numerical results show that the proposed Max-Min MCA-RZF precoder achieves a substantially higher network-wide minimum rate than the MCA-RZF and the conventional RZF precoders with uniform power allocation, respectively, as well as the conventional RZF precoder with Max-Min power allocation.