Blind Channel Estimation Based on Maximizing the Eigenvalue Spread of Cumulant Matrices in (2x1) Alamouti's Coding Schemes
Résumé
The popular Alamouti orthogonal space time code attains full transmit diversity in multiple antenna systems. This paper addresses the problem of blind channel identification in (2x1) Alamouti coded systems. Under the assumption of independent symbol substreams, the channel can be estimated from the eigendecomposition of matrices composed of second- or higher-order statistics (cumulants) of the received signal. The so-called joint approximate diagonalization of eigenmatrices (JADE) method for blind source separation via independent component analysis is optimal in that it tries to simultaneously diagonalize a full set of fourth-order cumulant matrices. To reduce computational complexity, we perform the eigenvalue decomposition of a single cumulant matrix, which is judiciously chosen by maximizing its expected eigenvalue spread. Simulation results show that the resulting technique outperforms existing blind Alamouti channel estimation methods and achieves a performance close to JADE's at a fraction of the computational cost.