Downlink channel spatial covariance estimation in realistic FDD massive MIMO systems

TL;DR

This paper introduces a novel method for estimating downlink channel spatial covariance in realistic FDD massive MIMO systems, accounting for 3D propagation and dual-polarized antennas, which improves over traditional UL-based estimation methods.

Contribution

The paper presents a new technique for DL covariance estimation that considers complex propagation effects and dual polarization, enhancing accuracy in modern 4G/5G systems.

Findings

The proposed method effectively estimates DL covariance in complex environments.

Numerical simulations demonstrate improved accuracy over existing approaches.

The approach is suitable for modern 4G and 5G massive MIMO deployments.

Abstract

The knowledge of the downlink (DL) channel spatial covariance matrix at the BS is of fundamental importance for large-scale array systems operating in frequency division duplexing (FDD) mode. In particular, this knowledge plays a key role in the DL channel state information (CSI) acquisition. In the massive MIMO regime, traditional schemes based on DL pilots are severely limited by the covariance feedback and the DL training overhead. To overcome this problem, many authors have proposed to obtain an estimate of the DL spatial covariance based on uplink (UL) measurements. However, many of these approaches rely on simple channel models, and they are difficult to extend to more complex models that take into account important effects of propagation in 3D environments and of dual-polarized antenna arrays. In this study we propose a novel technique that takes into account the aforementioned effects, in compliance with the requirements of modern 4G and 5G system designs. Numerical simulations show the effectiveness of our approach.