Eigenvector algorithm for blind MA system identification

Abstract We present a novel approach to the blind estimation of a linear time-invariant possibly mixed-phase moving average (MA) system (channel) based on second and fourth order statistics of the stationary received signal. As the algorithm incorporates the solution of an eigenvector problem, it is termed E igen V ector approach to blind I dentification (EVI). One of EVI’s main features is its ability to obtain reliable estimates of the channel’s MA parameters on the basis of very short records of received data samples. It is also robust with respect to an overestimation of the channel order. Furthermore, we demonstrate that, if independent additive white Gaussian noise is present, the degradation of the MA parameter estimates is minor even at low signal-to-noise ratios. By simulation results, we finally show the potential applicability of EVI to mobile radio communication channels under time-invariance conditions typically assumed in GSM receivers.

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