Covariance Matrix Estimation for Massive MIMO

Karthik Upadhya, Sergiy A. Vorobyov

Research output: Contribution to journalArticleScientificpeer-review

25 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)546-550
Number of pages5
JournalIEEE Signal Processing Letters
Issue number4
Publication statusPublished - Apr 2018
MoE publication typeA1 Journal article-refereed


  • Channel estimation
  • Coherence
  • Contamination
  • covariance estimation
  • Covariance matrices
  • Estimation
  • Massive MIMO
  • MIMO communication
  • Partial transmit sequences
  • pilot contamination
  • staggered pilots


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