Abstract

This work concerns wireless cellular networks applying time division duplexing (TDD) massive multiple-input multiple-output (MIMO) technology. Such systems suffer from pilot contamination during channel estimation, due to the shortage of orthogonal pilot sequences. This paper presents a solution based on pilot sequence hopping, which provides a randomization of the pilot contamination. It is shown that such randomized contamination can be significantly suppressed through appropriate filtering. The resulting channel estimation scheme requires no inter-cell coordination, which is a strong advantage for practical implementations. Comparisons with conventional estimation methods show that the MSE can be lowered as much as an order of magnitude at low mobility. Achievable uplink and downlink rates are increased by 42 and 46%, respectively, in a system with 128 antennas at the base station.

Highlights

  • Muliple-input multiple-output (MIMO) technology [1] is finding its way into practical systems, like LTE and its successor LTE-Advanced

  • 4 Analysis Initially, we present a simplified analysis of a toy example, in order to help the understanding of the benefit from pilot sequence hopping

  • We evaluate the achievable rates in a system with perfect channel state information (CSI) at the base station (BS) and a system with CSI achieved with a conventional minimum mean squared error (MMSE) estimator at the BS

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Summary

Introduction

Muliple-input multiple-output (MIMO) technology [1] is finding its way into practical systems, like LTE and its successor LTE-Advanced. Each BS performs linear combinations of messages intended for users applying the same pilot sequence This is shown to eliminate interference when the number of BS antennas goes to infinity. We propose pilot decontamination, which does not require inter-cell coordination and is able to exploit past pilot signals. It is based on pilot sequence hopping performed within each cell. The key in our solution is a channel estimation that incorporates multiple time slots so that it can benefit from randomization of the pilot contamination. Recent work utilizing temporal correlation for channel estimation is found in [13], not in combination with pilot hopping and not with the purpose of mitigating pilot contamination.

Channel model
Kalman filtering
Pilot sequence hopping
Bayesian analysis
Conclusions
Full Text
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