A Schur method for multiuser multichannel blind identification

We address the problem of blind multiuser multichannel identification in a Spatial Division Multiple Access (S.D.M.A.) context Using a stochastic model for the input symbols and only second-order statistics, we develop a simple algorithm, based on the Generalized Schur algorithm to apply LDU decomposition of the covariance matrix of the received data. We show that this method leads to identification of the channel, up to a unitary mixture matrix. Furthermore, the identification algorithm is shown to be robust to channel length overestimation and approaches the performance of the Weighted Linear prediction (WLP) method ill, at low computational cost.