Skip to main content
Log in

Adaptive decorrelating detectors for CDMA systems

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Multi-user detection allows for the efficient use of bandwidth in Code-Division Multiple-Access (CDMA) channels through mitigation of near-far effects and multiple-access noise limitations. Due to its inherent noise and multipath immunity, CDMA multi-access is being considered as a platform for personal communication systems (PCS). As CDMA based digital communication networks proliferate, the need to determine the presence of a new user and integrate knowledge of this new user into the detection scheme becomes more important. The decorrelating detector is a linear multi-user detector that is asymptotically optimal in terms of near far resistance; however, in the presence of a new unknown user, performance of the decorrelator is severely degraded. Adaptive decorrelators are constructed which adaptively augment an existing conventional decorrelator to demodulate a new active user in addition to existing users. Several likelihood ratio based schemes are employed. Both synchronous and asynchronous communication are investigated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. M. Basseville and I. V. Nikiforov,Detection of Abrupt Changes: Theory and Application. Englewood Cliffs: Prentice Hall, 1993.

    Google Scholar 

  2. K. W. Halford and M. Brandt-Pearce, “User identification and multiuser detection ofl out ofk users in a CDMA system,” inProceedings of the Twenty-eighth Annual Conference on Information Sciences and Systems, Princeton University, New Jersey, pp. 115–120, 1994.

    Google Scholar 

  3. R. A. Horn and C. R. Johnson,Matrix Analysis. Cambridge: Cambridge University Press, 1985.

    Google Scholar 

  4. A. Householder,The Theory of Matrices in Numerical Analysis. New York: Blaisdell Press, 1964.

    Google Scholar 

  5. D. Kazakos, “Asymptotic error probability expressions for multihypothesis testing using multisensor data,”IEEE Transactions on Systems, Man, and Cybernetics, Vol. 21, pp. 1101–1114, 1991.

    Google Scholar 

  6. D. G. Luenberger,Optimization by Vector Space Methods. New York: John Wiley & Sons, 1969.

    Google Scholar 

  7. R. Lupas and S. Verdú, “Linear multiuser detectors for synchronous code-division multiple-access channels,”IEEE Trans. Inform. Theory, Vol. 35, pp. 123–136, 1989.

    Google Scholar 

  8. R. Lupas and S. Verdú, “Near-far resistance of multi-user detectors in asynchronous channels,”IEEE Trans. on Comm., Vol. 38, pp. 496–508, 1990.

    Google Scholar 

  9. U. Mitra and H. V. Poor, “Analysis of an adaptive decorrelating detector for synchronous CDMA channels,” inProceedings of the Seventh IEE European Conference on Mobile Radio and Personal communications, Brighton, UK, December 1993, pp. 155–160, IEE, 1993.

  10. U. Mitra and H. V. Poor, “Detection of spread-spectrum signals in a multi-user environment,” inProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Detroit, May 1995.

  11. U. Mitra and H. V. Poor, “Activity detection in a multi-user environment,”Wireless Personal Communications, to appear in special issue on “Signal Separation and Interference Cancellation for Personal, Indoor and Mobile radio Communications”, in press.

  12. U. Mitra,Adaptive Multi-User Detection. PhD thesis, Princeton University, June 1994.

  13. H. V. Poor,An Introduction to Signal Detection and Estimation. New York: Springer-Verlag, 2nd ed., 1994.

    Google Scholar 

  14. D. V. Sarwate and M. B. Pursley, “Crosscorrelation properties of pseudorandom and related sequences,”Proc. IEEE, Vol. 68, pp. 593–619, 1980.

    Google Scholar 

  15. D. L. Schilling, R. L. Pickholtz and L. B. Milstein, “Spread spectrum goes commercial,”IEEE Spectrum, pp. 40–45, 1990.

  16. D. Slepian, “The one-sided barrier problem for Gaussian noise,”The Bell System Technical Journal, Vol. 41, pp. 463–501, 1962.

    Google Scholar 

  17. A. Stuart, “Equally correlated variates and the multinormal integral,”Journal of the Royal Statistical Society, Vol. 20, pp. 373–378, 1958.

    Google Scholar 

  18. S. Verdú, “Minimum probability of error for asynchronous Gaussian multiple-access channels,”IEEE Trans. Inform. Theory, Vol. 32, pp. 85–96, 1986.

    Google Scholar 

  19. S. Verdú, “Recent progress in multi-user detection,” in1988 Conference Proceedings, International Conference on Advances in Communications and Control Systems and Lecture Notes in Control and Information Sciences Series, Vol. 129, NY: Springer Verlag, 1988, IEEE, 1988.

    Google Scholar 

  20. A. Wald,Sequential Analysis. New York: Wiley, 1947.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

This research was supported by the U.S. Army Research Office under Grant DAAH04-93-G-0219.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mitra, U., Poor, H.V. Adaptive decorrelating detectors for CDMA systems. Wireless Pers Commun 2, 265–290 (1995). https://doi.org/10.1007/BF01099636

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01099636

Key words

Navigation