Toeplitz structured subspace for multi-channel blind identification methods

This paper addresses the problem of blind identification of multichannel systems. It proposes three different novel algorithms by exploiting the inherent Toeplitz /Sylvester structures impeded in the system model. The first algorithm is the structured signal subspace (SSS) method, which involves direct estimation of the signal from a multiple-input multiple-output (MIMO) system. The second algorithm is the structured channel subspace (SCS) method, whereby the MIMO channel matrix is estimated by employing its embedded Toeplitz structure. The last algorithm deals with the bilinear blind identification by utilizing the information (embedded structure) of both row and column subspaces of the received signals. The proposed methods exploit the block Sylvester structure of the signal and the channel matrix to formulate a quadratic cost function whose minimization enables us to estimate the desired system parameters. The simulation results of the proposed structured subspace methods are appealing in different scenarios.