Distributed Precoding Using Local CSIT for MU-MIMO Heterogeneous Cellular Networks

TL;DR

This paper introduces a distributed precoding method for MU-MIMO cellular networks that maximizes SILNR using only local CSIT, significantly improving spectral efficiency and approaching cooperative bounds.

Contribution

The paper proposes a novel distributed precoding technique based on SILNR maximization that works with local CSIT and approaches cooperative bounds in multi-cell MU-MIMO systems.

Findings

Outperforms existing noncooperative precoding methods.

Achieves near multi-cell cooperative bounds with limited antennas.

Robust to CSIT errors in multi-cell scenarios.

Abstract

Cell densification is a key driver to increase area spectral efficiencies in multi-antenna cellular systems. As increasing the densities of base stations (BSs) and users that share the same spectrum, however, both inter-user-interference (IUI) and inter-cell interference (ICI) problems give rise to a significant loss in spectral efficiencies in such systems. To resolve this problem under the constraint of local channel state information per BS, in this paper, we present a novel noncooperative multi-user multiple-input multiple-output (MIMO) precoding technique, called signal-to-interference-pulse-leakage-pulse-noise-ratio (SILNR) maximization precoding. The key innovation of our distributed precoding method is to maximize the product of SILNRs of users per cell using local channel state information at the transmitter (CSIT). We show that our precoding technique only using local CSIT can asymptotically achieve the multi-cell cooperative bound attained by cooperative precoding using global CSIT in some cases. We also present a precoding algorithm that is robust to CSIT errors in multi-cell scenarios. By multi-cell system-level simulations, we demonstrate that our distributed precoding technique outperforms all existing noncooperative precoding methods considerably and can also achieve the multi-cell bound very tightly even with not-so-many antennas at BSs.