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Massive multiple-input multiple-output (MIMO) systems use antenna arrays witha large number of antenna elements to serve many different userssimultaneously. The large number of antennas in the system makes, however, thechannel state information (CSI) acquisition strategy design critical andparticularly challenging. Interestingly, in the context of massive MIMOsystems, channels exhibit a large degree of spatial correlation which resultsin strongly rank-deficient spatial covariance matrices at the base station(BS). With the final objective of analyzing the benefits of covariance-aideduplink multi-user CSI acquisition in massive MIMO systems, here we compare thechannel estimation mean-square error (MSE) for (i) conventional CSIacquisition, which does not assume any knowledge on the user spatial covariancematrices and uses orthogonal pilot sequences; and (ii) covariance-aided CSIacquisition, which exploits the individual covariance matrices for channelestimation and enables the use of non-orthogonal pilot sequences. We apply alarge-system analysis to the latter case, for which new asymptotic MSEexpressions are established under various assumptions on the distributions ofthe pilot sequences and on the covariance matrices. We link these expressionsto those describing the estimation MSE of conventional CSI acquisition withorthogonal pilot sequences of some equivalent length. This analysis providesinsights on how much training overhead can be reduced with respect to theconventional strategy when a covariance-aided approach is adopted.

Covariance-Aided CSI Acquisition with Non-Orthogonal Pilots in Massive MIMO: A Large-System Performance Analysis