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 Cramáer-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.
Bibliographical noteFunding Information:
Manuscript received July 21, 2003; revised March 25, 2004. The work of A. B. Gershman was supported by the Wolfgang Paul Award Program of the Alexander von Humboldt Foundation, Germany; the Natural Sciences and Engineering Research Council (NSERC) of Canada; Communications and Information Technology Ontario (CITO); and the Premier’s Research Excellence Award Program of the Ministry of Energy, Science, and Technology (MEST) of Ontario. The work of N. D. Sidiropoulos was supported by the Army Research Laboratory through participation in the ARL Collaborative Technology Alliance (ARL-CTA) for Communications and Networks under Cooperative Agreement DADD19-01-2-0011. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Constantinos B. Papadias.
- Blind spatial signature estimation
- Parallel factor analysis
- Sensor array processing