Fourth-order tensor method for blind spatial signature estimation

In this paper, we consider a wireless communication scenario where M sources simultaneously transmit towards a base station equipped with an array of K sensors. A new method is proposed to solve the spatial signature estimation problem without resorting to training sequences and without knowledge of sources´ covariance structure. By assuming that the sources´ amplitudes vary between successive time blocks, a fourth-order tensor decomposition of the multimode spatio-temporal data covariance is proposed, from which an iterative algorithm is formulated to estimate sources´ spatial signatures. A distinguishing feature of the proposed tensor method is its efficiency in treating the case where the sources´ covariance matrix is non-diagonal and unknown, which generally happens when working with sample data covariances computed from a reduced number of snapshots.