Open Access

Blind PARAFAC Signal Detection for Polarization Sensitive Array

EURASIP Journal on Advances in Signal Processing20072007:012025

Received: 27 September 2006

Accepted: 16 April 2007

Published: 30 May 2007


This paper links the polarization-sensitive-array signal detection problem to the parallel factor (PARAFAC) model, which is an analysis tool rooted in psychometrics and chemometrics. Exploiting this link, it derives a deterministic PARAFAC signal detection algorithm. The proposed PARAFAC signal detection algorithm fully utilizes the polarization, spatial and temporal diversities, and supports small sample sizes. The PARAFAC algorithm does not require direction-of-arrival (DOA) information and polarization information, so it has blind and robust characteristics. The simulation results reveal that the performance of blind PARAFAC signal detection algorithm for polarization sensitive array is close to nonblind MMSE method, and this algorithm works well in array error condition.


Authors’ Affiliations

Electronic Engineering Department, Nanjing University of Aeronautics and Astronautics


  1. Ng JWP, Monikas A: Polarisation-sensitive array in blind MIMO CDMA system. Electronics Letters 2005,41(17):970-972. 10.1049/el:20052371View ArticleGoogle Scholar
  2. Kaptsis I, Balmain KG: Base station polarization-sensitive adaptive antenna for mobile radio. Proceedings of the 3rd Annual International Conference on Universal Personal Communications (ICUPC '94), September-October 1994, San Diego, Calif, USA 230-235.Google Scholar
  3. Weiss AJ, Friedlander B: Maximum likelihood signal estimation for polarization sensitive arrays. IEEE Transactions on Antennas and Propagation 1993,41(7):918-925. 10.1109/8.237623View ArticleGoogle Scholar
  4. Zhenhai X, Xuesong W, Shunping X, Zhuang Z: Filtering performance of polarization sensitive array: completely polarized case. Acta Electronica Sinica 2004,32(8):1310-1313.Google Scholar
  5. Smilde A, Bro R, Geladi P: Multi-Way Analysis. Applications in the Chemical Sciences. John Wiley & Sons, Chichester, UK; 2004.View ArticleGoogle Scholar
  6. Harshman RA: Foundations of the PARAFAC procedure: model and conditions for an 'explanatory' multi-mode factor analysis. UCLA Working Papers Phonetics 1970,16(1):1-84.Google Scholar
  7. Carroll JD, Chang J-J: Analysis of individual differences in multidimensional scaling via an n-way generalization of "Eckart-Young" decomposition. Psychometrika 1970,35(3):283-319. 10.1007/BF02310791View ArticleMATHGoogle Scholar
  8. De Lathauwer L, De Moor B, Vandewalle J: Computation of the canonical decomposition by means of a simultaneous generalized Schur decomposition. SIAM Journal on Matrix Analysis and Applications 2004,26(2):295-327. 10.1137/S089547980139786XMathSciNetView ArticleMATHGoogle Scholar
  9. De Lathauwer L: A link between the canonical decomposition in multilinear algebra and simultaneous matrix diagonalization. SIAM Journal on Matrix Analysis and Applications 2006,28(3):642-666. 10.1137/040608830MathSciNetView ArticleMATHGoogle Scholar
  10. Kruskal JB: Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics. Linear Algebra and Its Applications 1977,18(2):95-138. 10.1016/0024-3795(77)90069-6MathSciNetView ArticleMATHGoogle Scholar
  11. Sidiropoulos ND, Giannakis GB, Bro R: Blind PARAFAC receivers for DS-CDMA systems. IEEE Transactions on Signal Processing 2000,48(3):810-823. 10.1109/78.824675View ArticleGoogle Scholar
  12. Sidiropoulos ND, Bro R, Giannakis GB: Parallel factor analysis in sensor array processing. IEEE Transactions on Signal Processing 2000,48(8):2377-2388. 10.1109/78.852018View ArticleGoogle Scholar
  13. Rong Y, Vorobyov SA, Gershman AB, Sidiropoulos ND: Blind spatial signature estimation via time-varying user power loading and parallel factor analysis. IEEE Transactions on Signal Processing 2005,53(5):1697-1710.MathSciNetView ArticleGoogle Scholar
  14. Yu Y, Petropulu AP: Parafac based blind estimation of MIMO systems with possibly more inputs than outputs. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '06), May 2006, Toulouse, France 3: 133-136.Google Scholar
  15. Mokios KN, Sidiropoulos ND, Potamianos A: Blind speech separation using parafac analysis and integer least squares. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '06), May 2006, Toulouse, France 5: 73-76.Google Scholar
  16. Zhang X, Xu D: Blind PARAFAC receiver for space-time block-coded CDMA system. Proceedings of International Conference on Communications, Circuits and Systems, June 2006, Guilin, Guangzi, China 2: 675-678.Google Scholar
  17. Zhang X, Xu D: PARAFAC multiuser detection for SIMO-CDMA system. Proceedings of International Conference on Communications, Circuits and Systems, June 2006, Guilin, Guangzi, China 2: 744-747.Google Scholar
  18. Vorobyov SA, Rong Y, Sidiropoulos ND, Gershman AB: Robust iterative fitting of multilinear models. IEEE Transactions on Signal Processing 2005,53(8, part 1):2678-2689.MathSciNetView ArticleGoogle Scholar
  19. Tomasi G, Bro R: A comparison of algorithms for fitting the PARAFAC model. Computational Statistics & Data Analysis 2006,50(7):1700-1734. 10.1016/j.csda.2004.11.013MathSciNetView ArticleMATHGoogle Scholar
  20. Sidiropoulos ND, Liu X: Identifiability results for blind beamforming in incoherent multipath with small delay spread. IEEE Transactions on Signal Processing 2001,49(1):228-236. 10.1109/78.890366View ArticleGoogle Scholar
  21. Proakis JG: Digital Communications. 3rd edition. McGraw-Hill, New York, NY, USA; 1995.MATHGoogle Scholar
  22. Leurgans SE, Ross RT, Abel RB: A decomposition for three-way arrays. SIAM Journal on Matrix Analysis and Applications 1993,14(4):1064-1083. 10.1137/0614071MathSciNetView ArticleMATHGoogle Scholar
  23. Sanchez E, Kowalski BR: Tensorial resolution: a direct trilinear decomposition. Journal of Chemometrics 1990,4(1):29-45. 10.1002/cem.1180040105View ArticleGoogle Scholar
  24. Gesbert D, Sorelius J, Paulraj A: Blind multi-user MMSE detection of CDMA signals. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '98), May 1998, Seattle, Wash, USA 6: 3161-3164.Google Scholar
  25. Tsatsanis MK, Xu Z: Performance analysis of minimum variance CDMA receivers. IEEE Transactions on Signal Processing 1998,46(11):3014-3022. 10.1109/78.726814View ArticleGoogle Scholar


© X. Zhang and D. Xu. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.