Covariance Matrix Estimation for Massive MIMO

Abstract

We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.

arXiv comment6 pages, 4 figures. Accepted for publication in IEEE Signal Processing Letters

References in corpus (7)

• Massive MIMO for Next Generation Wireless Systems
• Scaling up MIMO: Opportunities and Challenges with Very Large Arrays
• A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems
• Blind pilot decontamination
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• Covariance Matrix Estimation for Massive MIMO
• User Subgrouping and Power Control for Multicast Massive MIMO over Spatially Correlated Channels
• Spectral Efficiency Analysis of Cell-free Distributed Massive MIMO Systems with Imperfect Covariance Matrix