A NOVEL APPROACH BASED ON NON-UNITARY JOINT BLOCK-DIAGONALIZATION FOR THE BLIND MIMO EQUALIZATION OF CYCLO-STATIONARY SIGNALS

In this paper, we address the problem of the blind separation of convolutive mixtures of sources also known as blind equal-ization of linear time invariant multi-input multi-output sys-tems in digital communications. In our case, the considered input signals are cyclo-stationary processes whose cyclic fre-quencies are not necessarily known. To tackle that problem, we propose to use a new algorithm that performs the (non-unitary) joint block diagonalization (JBD) of a given set of complex matrices. It is based on a gradient approach. But first, the matrices set to be joint block-diagonalized has to be built: this is done using a particular linear operator on the correlation matrices of the observations and taking advan-tage of some specific algebraic properties of the aforemen-tioned “transformed ” matrices (for instance, the frequencies that correspond to the matrices belonging to that set happen to be the cyclic ones). Then, the JBD of this matrices set enables to estimate the mixing system and, consequently, to recover the source signals. Computer simulations are pro-vided in order to illustrate the behavior and the usefulness of the proposed approach in the context of digital commu-nications and a comparison with another existing method is also performed. 1