Emergent Mind

Pilot Pattern Adaptation for 5G MU-MIMO Wireless Communications

(1605.05061)
Published May 17, 2016 in cs.IT and math.IT

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.

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