Pilot Pattern Adaptation for 5G MU-MIMO Wireless Communications

TL;DR

This paper proposes a scheme for adapting pilot patterns in 5G MU-MIMO systems to reduce channel state information overhead, enhancing spectral efficiency by optimizing resource allocation based on user groups and resource blocks.

Contribution

It introduces a practical grouping-based pilot pattern adaptation scheme for MU-MIMO, improving spectral efficiency over fixed pilot patterns in 5G systems.

Findings

Significant spectral efficiency gains demonstrated through analytical and numerical evaluations.

Adaptive pilot pattern scheme reduces CSI overhead without compromising channel estimation quality.

Grouping users based on channel conditions enhances MU-MIMO performance.

Abstract

To meet the goal of ten-fold increase in spectral efficiency, multiuser multiple-input-multiple-output (MU-MIMO) techniques capable of achieving high spatial multiplexing gains are expected to be an essential component of fifth-generation (5G) radio access systems. This increase in multiplexing gain, made possible by equipping base stations with a large number of antennas, entails a proportional increase in channel state information (CSI) acquisition overhead. This article addresses the problem of reducing this CSI overhead by optimizing the amount of time-frequency resources allocated for channel training purposes while not affecting the quality of the associated channel estimate. First we show that in MU-MIMO, adapting pilot symbol density in the time-frequency grid should be performed both on a per resource block (RB) basis and on the basis of groups of users sharing similar channel conditions. Next, we propose a practical scheme that can perform grouping based per-RB pilot pattern adaptation. Finally, we evaluate using both analytical and numerical results the gain in spectral efficiency that can be achieved using this scheme as compared to conventional MU-MIMO systems that use fixed pilot patterns.