Journal of Multivariate Analysis
Improved subspace DoA estimation methods with large arrays: The deterministic signals case
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
On the capacity achieving covariance matrix for Rician MIMO channels: an asymptotic approach
IEEE Transactions on Information Theory
Channel Capacity Estimation Using Free-Probability Theory
IEEE Transactions on Signal Processing
Asymptotic Mutual Information Statistics of Separately Correlated Rician Fading MIMO Channels
IEEE Transactions on Information Theory
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In this paper, we deal with the estimation of the ergodic capacity of large MIMO systems, using training sequences whose lengths are of the same order of magnitude than the number of antennas. In this context, the traditional estimator becomes inconsistent. Following the ideas developed by Girko in the context of the so-called theory of G-estimation, we propose a new estimator. We analyze its asymptotic behaviour and show, using numerical simulations, that it tends to improve significantly the performance of the standard estimate for a realistic number of antennas.