The optimum solution is using all degrees of freedom by processing the adaptive filter on the antenna elements. For adaptive direct methods, Sample Matrix Inversion (SMI) uses the estimated (sample) interference covariance matrix in place of the actual interference covariance matrix. This is because the actual interference covariance matrix is not known in practice. If it is known by some means, then it need not be estimated, and the optimal weights are fixed. This is sometimes called the data-independent variation. The data-dependent variation estimates the interference covariance matrix from the data. In MIMO communications systems, this can be done via a training sequence. The clairvoyant detector is given when the covariance matrix is known perfectly and defined as: