Simple Framework of ZF Precoding Analysis for Full-Dimensional Massive MIMO Systems

TL;DR

This paper introduces a simple, accurate framework for analyzing ZF precoding in full-dimensional massive MIMO systems, accounting for realistic propagation models and user correlations, providing practical insights into system performance.

Contribution

It presents a novel Neumann series-based analytical framework for ZF precoding performance that considers finite multipath and user correlation effects.

Findings

Optimal UE separation angles are around 30° azimuth and 15° elevation.

The framework accurately predicts performance degradation due to channel correlation.

Insights on how propagation parameters influence ZF performance.

Abstract

We provide a simple, yet general and accurate framework for analyzing zero-forcing (ZF) precoding performance for a full-dimensional massive multiple-input multiple-output system. Exploiting an order two Neumann series, our framework approximates the expected (average) ZF signal-to-noise ratio and ergodic sum spectral efficiency, while catering for a finite multipath propagation model, as well as correlated and uncorrelated user equipment (UE) positions in both azimuth and elevation domains. The analysis provides clear insights on the influence of propagation and system parameters on ZF performance. We identify how far UEs must lie in azimuth and elevation for the ZF precoder to approach uncorrelated channels. Our framework is useful for predicting the ZF performance degradation arising from channel correlation. For optimal performance, UEs could be separated by around 30$^\circ$ in azimuth and 15$^\circ$ in elevation - conditions which are difficult to meet in reality.