Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
권호 표지

A Novel Subspace Tracking Algorithm and Its Application to Blind Multiuser Detection in Cellular CDMA Systems

  • Ali, Imran (Center for Advance Studies in Telecommunication, COMSATS Institute of Information Technology) ;
  • Kim, Doug-Nyun (Digital Communication Lab., Myongji University) ;
  • Song, Yun-Jeong (Next Mobile Broadcasting Technology Research Team, ETRI) ;
  • Azeemi, Naeem Zafar (Center for Advance Studies in Telecommunication, COMSATS Institute of Information Technology)
  • Received : 2008.06.24
  • Accepted : 2010.01.21
  • Published : 2010.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose and develop a new algorithm for the principle subspace tracking by orthonormalizing the eigenvectors using an approximation of Gram-Schmidt procedure. We carry out a novel mathematical derivation to show that when this approximated version of Gram-Schmidt procedure is added to a modified form of projection approximation subspace tracking deflation (PASTd) algorithm, the eigenvectors can be orthonormalized within a linear computational complexity. While the PASTd algorithm tries to extracts orthonormalized eigenvectors, the new scheme orthonormalizes the eigenvectors after their extraction, yielding much more tacking efficiency. We apply the new tracking scheme for blind adaptive multiuser detection for non-stationary cellular CDMA environment and use extensive simulation results to demonstrate the performance improvement of the proposed scheme.

Keywords

References

  1. F. Gao, Y. Zeng, A. Nallanathan, and T.-S. Ng, "Robust subspace blind channel estimation for cyclic prefixed MIMO ODFM systems: Algorithm, identifiability and performance analysis," IEEE J. Sel. Areas Commun., vol. 26, no. 2, pp. 378–388, Feb. 2008. https://doi.org/10.1109/JSAC.2008.080214
  2. W. Kang and B. Champagne, "Generalized blind subspace channel estimation," in Proc. IEEE VTC, Oct. 2003, pp. 1209–1213.
  3. J. Namgoong, T. F.Wong, and J. S. Lehnert, "Subspace multiuser detection for multicarrier DS-CDMA," IEEE Trans. Commun., vol. 48, no 11, pp. 1897–1908, Nov. 2000. https://doi.org/10.1109/26.891207
  4. M. Jansson, B. Goransson, and B. Ottersten, "A subspace method for direction of arrival estimation of uncorrelated emitter signals," IEEE Trans. Signal Process., vol. 47, no. 4, pp. 945–956, Apr. 1999
  5. D. Kotoulas, P. Koukoulas, and N. Kalouptsidis, "Subspace projection based blind channel order estimation ofMIMO systems," IEEE Trans. Signal Process., vol. 54, no. 4, pp. 1351–1363, Apr. 2006. https://doi.org/10.1109/TSP.2005.863104
  6. B. Yang, "Projection approximation subspace tracking," IEEE Trans. Signal Process., vol. 43, No. 1, pp. 95–107, Jan. 1995. https://doi.org/10.1109/78.365290
  7. P. Strobach, "Low-rank adaptive filters," IEEE Trans. Signal Process., vol. 44, no. 12, pp. 2932–2947, Dec. 1996. https://doi.org/10.1109/78.553469
  8. R. Badeau, B. David, and G. Richard, "Fast approximated power iteration subspace tracking," IEEE Trans. Signal Process., vol. 53, no. 8, pp. 2931– 2941, Aug. 2005. https://doi.org/10.1109/TSP.2005.850378
  9. M. Moonen, P. V. Dooren, and J. Vandewalle, "An SVD updating algorithm for subspace tracking," SIAM J. Matrix Anal. Appl., vol. 13, no. 4, pp. 1015–1038, 1992. https://doi.org/10.1137/0613061
  10. X. G. Doukopoulos and G. V. Moustakides, "Fast and stable subspace tracking," IEEE Trans. Signal Process., vol. 56, no. 4, pp. 1452–1465, Apr. 2008. https://doi.org/10.1109/TSP.2007.909335
  11. Z. Fu and E. M. Dowling, "Conjugate gradient projection subspace tracking," IEEE Trans. Signal Process., vol. 45, no. 6, pp. 1664–1668, June 1997. https://doi.org/10.1109/78.600010
  12. P. Strobach, "Bi-iteration SVD subspace tracking algorithms," IEEE Trans. Signal Process., vol. 45, no. 5, pp. 1222–1240 May 1997. https://doi.org/10.1109/78.575696
  13. K. Abed-Meraim, A. Chkeif, and Y. Hua, "Fast orthonormal PAST algorithm," IEEE Signal Process. Lett., vol. 7, no. 3, pp. 60–62, Mar. 2000. https://doi.org/10.1109/97.823526
  14. R. Badeau, G. Richard, and B. David, "Approximated power iterations for fast subspace tracking," in Proc. 7th Int. Symp. Signal Process. Appl., vol. 2, July 2003, pp. 583–586.
  15. X. Wang and H. V. Poor, "Blind multiuser detection: A subspace approach," IEEE Trans. Inf. Theory, vol. 44, pp. 677–691, Mar. 1998. https://doi.org/10.1109/18.661512
  16. E. Oja and J. Karhunen., "On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix," Helsinki University of Technology,Dept. of Technical Physics, Rep. TKKF-A458, 1981.
  17. E. Oja and J. Karhunen., "On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix," J. Mathematical Anal. Appl., vol. 106, no. 1, pp. 69–84, 1985. https://doi.org/10.1016/0022-247X(85)90131-3
  18. X. Wang and H. V. Poor, "Blind adaptive multiuser detection in multipath CDMA channels based on subspace tracking," IEEE Trans. Signal Process., vol. 46, pp. 3030–3044, Nov. 1998. https://doi.org/10.1109/78.726816
  19. J. G. Proakis, Digital Communications, 3rd ed. New York: McGraw Hill, 1995
  20. S. Attallah and K. Abed-Meriam, "Fast algorithms for subspace tracking," IEEE Signal Process. Lett., vol. 8, No. 7, pp. 203–206, July 2001. https://doi.org/10.1109/97.928678
  21. G. H. Gloub and C. F. Van Loan, Matrix Computation, 3rd ed. John Hopkins Univ. Press, Baltimore, 1996.
  22. X.-D. Zhang and W. Wei, "Blind adaptive multiuser detection based on Kalman filtering," IEEE Trans. Signal Process., vol. 50, no. 1, pp. 87–95, Jan. 2002. https://doi.org/10.1109/78.972485