Journal of Communications and Networks

The Korean Institute of Commucations and Information Sciences (한국통신학회)
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Multiuser Channel Estimation Using Robust Recursive Filters for CDMA System

  • Kim, Jang-Sub (Department of Electrical Engineering, Texas A&M University) ;
  • Shin, Ho-Jin (School of Information and Communications Engineering, Sungkyunkwan University) ;
  • Shin, Dong-Ryeol (School of Information and Communications Engineering, Sungkyunkwan University)
  • Published : 2007.09.30
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Abstract

In this paper, we present a novel blind adaptive multiuser detector structure and three robust recursive filters to improve the performance in CDMA environments: Sigma point kalman filter (SPKF), particle filter (PF), and Gaussian mixture sigma point particle filter (GMSPPF). Our proposed robust recursive filters have superior performance over a conventional extended Kalman filter (EKF). The proposed multiuser detector algorithms initially use Kalman prediction form to estimated channel parameters, and unknown data symbol be predicted. Second, based on this predicted data symbol, the robust recursive filters (e.g., GMSPPF) is a refined estimation of joint multipaths and time delays. With these estimated multipaths and time delays, data symbol detection is carried out (Kalman correction form). Computer simulations show that the proposed algorithms outperform the conventional blind multiuser detector with the EKF. Also we can see it provides a more viable means for tracking time-varying amplitudes and time delays in CDMA communication systems, compared to that of the EKF for near-far ratio of 20 dB. For this reason, it is believed that the proposed channel estimators can replace well-known filter such as the EKF.

Keywords

References

  1. A. Duel-Hallen et al., 'Multiuser Detection for CDMA System,' IEEE Personal Commun. Mag., pp. 46-58, Apr. 1995
  2. R. Lupas and S. Verdu, 'Linear multiuser detectors for synchronous codedivision multiple access channel,' IEEE Trans. Inf. Theory, vol. IT-35, pp. 123-136, Jan. 1989
  3. M. K. Varanasi and B. Aazhang, 'Near-optimum detection in synchronous code-division multiple access channel,' IEEE Trans. Commun., vol. COM-39, pp. 725-736, May 1991
  4. A. Duen-Hallen, 'Decorrelating decision-feedback multiuser detector for synchronous code-division multiple access channel,' IEEE Trans. Commun., vol. COM-41, pp. 285-290, Feb. 1993
  5. P. Patel and J. Holtzman, 'Analysis of a simple successive interference cancellation scheme in DS/CDMA system,' IEEE J. Sel. Areas Commun. - Special issue on CDMA, vol. 12, pp. 796-807, June 1994 https://doi.org/10.1109/49.298053
  6. R. A. ILitis, 'Joint estimation of PN code delay and multipath using the extended Kalman filter,' IEEE Trans. Commun., vol. 38, Oct. 1990, pp. 1677-1685 https://doi.org/10.1109/26.61437
  7. R. A. lltis and L. Mailaender, 'An adaptive multiuser detector with joint amplitude and delay estimation,' IEEE J. Sel. Areas Commun., vol. 12, June 1994
  8. R. A. lltis, 'A DS-CDMA tracking mode receiver with joint channel/delay estimation and MMSE detection,' IEEE Trans. Commun., vol. 49, Oct. 2001
  9. R. van der Merwe and E. Wan, 'Efficient derivative-free Kalman filters for online learning,' in Proc. ESANN, Apr. 2001
  10. J. Jr. Caffery and G. L. Stuber, 'Nonlinear multiuser parameter estimation and tracking in CDMA systems,' IEEE Trans. Commun., vol. 48, pp. 2053-2063, Dec. 2000 https://doi.org/10.1109/26.891216
  11. R. van der Merwe et. al., 'The unscented particle filter,' Oregon Graduate Institute Electrical and Computer Engineering, vol. OR-97006, Aug. 2000
  12. J. Kim and et. al., 'Nonlinear multiuser parameter estimation by the scaled unscented filter in CDMA systems,' in proc. The 2004 Int. Conf. on Wireless Networks, June 2004
  13. R. Chen, X. Wang, and J.S. Liu, 'Adaptive joint detection and decoding in flat-fading channels via mixture Kalman filtering,' IEEE Trans. Inf. Theory, vol. 46, pp. 2079-2094, Sept. 2000 https://doi.org/10.1109/18.868479
  14. E. Punskaya et. al., 'Particle filtering for demodulation in fading channels with non-Gaussian additive noise,' IEEE Trans. Commun., vol. 49, pp. 579-582, Apr. 2001 https://doi.org/10.1109/26.917760
  15. E. Punskaya et. al., 'Particle filtering for multiuser detection in fading CDMA channels,' in Proc. IEEE 11th Signal Processing Workshop on Statistical Signal Processing, Aug. 2001
  16. T.Bertozzi et. al., 'Channel tracking using particle filtering in unresolvable multipath enrironrnents,' EURASIP J. Applied Signal Process., pp. 2328-2338, 2004
  17. R. A. lItis, 'A sequential monte carlo filter for joint linear/nonlinear state estimation with application to DS-CDMA,' IEEE Trans. Signal Process., vol. 51,pp.417-426,Feb. 2003 https://doi.org/10.1109/TSP.2002.806995
  18. E. Punskaya, A. Doucet, and W. J. Fitzgerald, 'Particle filtering for joint symbol and code delay estimation in DS spread spectrum systems in multipath environment,' EURASIP Applied Signal Process., pp. 2306-2314, 2004
  19. A. Doucet, 'On sequential simulation-based methods for bayesian filtering,' Tech. Report CUED/F-INFENG/TR 310, (Cambridge University), 1998
  20. M. Arulampalam et. al., 'A tutorial on particle filters for on-line nonlinear/non-gaussian bayesian tracking,' IEEE Trans. Signal Process., pp.174-188, Feb. 2002
  21. R. van der Merwe and E. Wan. 'Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models,' in Proc. ICASSP, Apr. 2003
  22. F. Pernkopf and D. Bouchaffra, 'Genetic-Based EM algorithm for learning gaussian mixture models,' IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, Aug. 2005
  23. T. S. Rappaport, Wireless Communications. New York: IEEE Press, 1996
  24. Kaveh Pahlavan and Allen H. Levesque, Wireless Information Networks. John Wiley & Sons, 1995
  25. Gordon L. Stuber, Principles of Mobile Communication. 2nd Ed. Kluwer Academic, 2001