Covariance Matrix Estimation for Massive MIMO
Research output: Contribution to journal › Article › Scientific › peer-review
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.
|Number of pages||5|
|Journal||IEEE Signal Processing Letters|
|Publication status||Published - Apr 2018|
|MoE publication type||A1 Journal article-refereed|
- Channel estimation, Coherence, Contamination, covariance estimation, Covariance matrices, Estimation, Massive MIMO, MIMO communication, Partial transmit sequences, pilot contamination, staggered pilots