Otherwise, the matrix is full rank.
Decoding is only possible if M innovative packets are received, i.e., when the decoding matrix is full rank.
It should be noted that this is only possible if matrix is full rank, and this is why (1) must be fulfilled.
However, such a strictly banded assumption is not true, and the channel matrix is full in nature especially at high Doppler spreads.
In view of the coefficient matrix being full or dense, the Gaussian elimination method is unfeasible because of its heavy computational and storage load.
The use of residuals for detecting departures from the assumptions of the linear model with full-rank covariance, whether the design matrix is full rank or not, has long been recognized as an important diagnostic tool.
The underidentification tests in all four 2SLS regressions reject the null hypothesis indicating that the reduced form coefficient matrix is full rank and the instruments are able to identify the model, satisfying the relevance assumption.
In (1), y' and x denote the received and transmitted signal vectors, respectively, and H ′ ∈ C N r × N t denotes the secondary users channel (in this article, we always assume that the channel matrix is full rank).
In this section, we assume that the speech covariance matrix is full rank, i.e., equal to L. We can still use the method presented in the previous section, but this time we should expect distortion of the desired signal.
