Blind PARAFAC signal detection for polarization sensitive array
EURASIP Journal on Applied Signal Processing
4D near-field source localization using cumulant
EURASIP Journal on Applied Signal Processing
Blind Joint Symbol Detection and DOA Estimation for OFDM System with Antenna Array
Wireless Personal Communications: An International Journal
A novel semiblind signal extraction approach for the removal of eye-blink artifact from EEGs
EURASIP Journal on Advances in Signal Processing
Classification of three-way data by the dissimilarity representation
Signal Processing
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In this paper, the problem of blind spatial signature estimation using the parallel factor (PARAFAC) analysis model is addressed in application to wireless communications. A time-varying user power loading in the uplink mode is proposed to make the model identifiable and to enable application of PARAFAC analysis. Then, identifiability issues are studied in detail and closed-form expressions for the corresponding modified Crame´r-Rao bound (CRB) are obtained. Furthermore, two blind spatial signature estimation algorithms are developed. The first technique is based on the PARAFAC fitting trilinear alternating least squares (TALS) regression procedure, whereas the second one makes use of the joint approximate diagonalization algorithm. These techniques do not require any knowledge of the propagation channel and/or sensor array manifold and are applicable to a more general class of scenarios than earlier approaches to blind spatial signature estimation.