Covariance Matrix Estimation in Massive MIMO

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Abstract
Interference during the uplink training phase significantly deteriorates the performance of a massive MIMO system. The impact of the interference can be reduced by exploiting second order statistics of the channel vectors, e.g., to obtain minimum mean squared error estimates of the channel. In practice, the channel covariance matrices have to be estimated. The estimation of the covariance matrices is also impeded by the interference during the training phase. However, the coherence interval of the covariance matrices is larger than that of the channel vectors. This allows us to derive methods for accurate covariance matrix estimation by appropriate assignment of pilot sequences to users in consecutive channel coherence intervals. To keep the computational complexity in check, we exploit common structure of the covariance matrices.
Funding Information
  • Agence Nationale de la Recherche (ANR-16-CE23-0014 (FBIMATRIX))

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