MIMO signal separation for FIR channels: a criterion and performance analysis

Signal separation for a general system of an arbitrary number of signals is investigated. The signal separation research area deals with the problem of separating unknown source signals that are mixed in an unknown way when only these mixtures are available. A criterion, based on second-order statistics, is formulated to be used in estimating the mixing system. This estimate of the mixing system is used in a separation structure with a parameterization that minimizes the number of parameters to be estimated. Formulae for the gradient and Hessian of the criterion are derived. A formula for the lower bound for the variance of the estimated parameters of the mixing matrix is derived. This lower bound is the asymptotic (assuming the number of data samples to be large) Cramér–Rao lower bound (CRLB). The proposed algorithm is tested with simulations and compared with the CRLB.