Skip to main content
Log in

Application of Sequential Estimation Algorithm Based on Branch Metric to Frequency-Selective Channel Equalization

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

In this work, a sequential estimation algorithm based on branch metric is used as channel equalizer to combat intersymbol interference in frequency-selective wireless communication channels. The bit error rate (BER) and computational complexity of the algorithm are compared with those of the maximum likelihood sequence estimation (MLSE), the recursive least squares (RLS) algorithm, the Fano sequential algorithm, the stack sequential algorithm, list-type MAP equalizer, soft-output sequential algorithm (SOSA) and maximum-likelihood soft-decision sequential decoding algorithm (MLSDA). The BER results have shown that whilst the sequential estimation algorithm has a close performance to the MLSE using the Viterbi algorithm, its performance is better than the other algorithms. Beside, the sequential estimation algorithm is the best in terms of computational complexity among the algorithms mentioned above, so it performs the channel equalization faster. Especially in M-ary modulated systems, the equalization speed of the algorithm increases exponentially when compared to those of the other algorithms.

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. Wozencraft J.M., Reiffen B. (1961) Sequential decoding. Massachusetts Institute of Technology Press, Cambridge, MA, pp 25–46

    MATH  Google Scholar 

  2. Viterbi J. (1967) Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory IT-13: 260–269

    Article  Google Scholar 

  3. Fano R.M. (1963) A heuristic discussion of probabilistic decoding. IEEE Transactions on Information Theory IT-9: 64–74

    Article  MathSciNet  Google Scholar 

  4. Zigangirov K.Sh. (1966) Some sequential decoding procedures. Problemy Peredachi Informatsii 2(4): 13–25

    Google Scholar 

  5. Jelinek F. (1969) Fast sequential decoding algorithm using a stack. IBM Journal of Research and Development 13: 675–678

    Article  MathSciNet  MATH  Google Scholar 

  6. Chevillat P.R., Costello D.J. Jr (1977) A multiple stack algorithm for erasurefree decoding of convolutional codes. IEEE Transactions on Communications C-25: 1460–1470

    Article  Google Scholar 

  7. Wei C., Riedel S., Hagenauer J. (1996) Sequential decoding using a priori information. Electronics Letters 32: 1190–1191

    Article  Google Scholar 

  8. Li K.P., Kallel S. (1999) A bidirectional multiple stack algorithm. IEEE Transactions on Communications C-47: 6–9

    Google Scholar 

  9. Haccoun D., Ferguson M.J. (1975) Generalized stack algorithms for decoding convolutional codes. IEEE Transactions on Information Theory IT-21: 638–651

    Article  Google Scholar 

  10. Johanesson R., Zigangirov K.Sh. (1999) Fundamentals of convolutional coding. IEEE Press, Piscataway, NJ

    Book  Google Scholar 

  11. Jacobs I.M., Berlekamp E.R. (1967) A lower bound to the distribution of computation for sequential decoding. IEEE Transactions on Information Theory IT-13: 167–174

    Article  Google Scholar 

  12. Forney G.D. Jr (1972) Maximum-likelihood sequence estimation of digital sequences in the presence of intersymbol interference. IEEE Transactions on Information Theory IT-18(3): 363–378

    Article  MathSciNet  Google Scholar 

  13. Widrow B., Kalman R.E., DeClaris N. (1970) Adaptive filters: Aspects of network and system theory. Holt, Rinehart and Winston, New York

    Google Scholar 

  14. Godard D.N. (1974) Channel equalization using a Kalman filter for fast data transmission. IBM Journal of Research & Development 18: 267–273

    Article  MATH  Google Scholar 

  15. Berrou, C., Glavieux, A., & Thitimajshima, P. (1993). Near shannon limit error-correcting coding and decoding: Turbo codes. In Proceeding of IEEE international conference on communications (pp. 1064–1070) Geneva, Switzerland.

  16. Xiong F., Zerik A., Shwedyk E. (1990) Sequential sequence estimation for channels with intersymbol interference of finite or infinite Length. IEEE Transactions on Communications 38(6): 795–804

    Article  Google Scholar 

  17. Xiong F., Dai Q.Y., Shwedyk E. (1993) Computational complexity of sequential sequence estimation for intersymbol interference channels. IEEE Transactions on Communications 41(2): 332–337

    Article  MATH  Google Scholar 

  18. Xiong F., Shwedyk E. (1993) Sequential sequence estimation for multiple-channel systems with intersymbol and interchannel interference. IEEE Transactions on Communications 41(2): 322–331

    Article  MATH  Google Scholar 

  19. Xiong F. (1995) Sequential decoding of convolutional codes in channels with intersymbol interference. IEEE Transactions on Communications 43(2/3/4): 828–836

    Article  MATH  Google Scholar 

  20. Haccoun D., Kallel S. (1991) Application of multiple path sequential decoding for intersymbol interference reduction problem. IEE Proceedings-I 138(1): 21–31

    Google Scholar 

  21. Tungsrisaguan, E., & Rajatheva, R. M. A. P. (2001). Soft-output sequential algorithm for signal estimation over frequency selective fading channel. In Global Telecommunications Conference, GLOBECOM ’01. IEEE 2 (pp.1241–1245).

  22. Han Y.S., Chen P.N., Wu H.B. (2002) A maximum-likelihood soft-decision sequential decoding algorithm for binary convolutional codes. IEEE Transactions on Communications C-50: 173–178

    Article  Google Scholar 

  23. Sellami, N., Siala, M., & Fijalkow, I. (2004). Low-complexity equalizers for MIMO frequency selective channels. In Control, communications and signal processing first international symposium (pp. 175–178).

  24. Penther, B., Castelain, D., & Kubo, H. (2000). A modified turbo-detector for long delay spread channels. In International symposium on turbo-codes, Brest, France.

  25. Çavdar T., Gangal A. (2007) A new sequential decoding algorithm based on branch metric. Wireless Personal Communications 43(4): 1093–1100

    Article  Google Scholar 

  26. Çavdar, T. (2003). A new sequential block data estimation algorithm and its performance analysis over frequency selective channels. Ph.D. dissertation, Department of Electronics Engineering, Karadeniz Technical University, Turkey.

  27. Proakis J.G. (2000) Digital communications (4th ed.). McGraw Hill, New York

    Google Scholar 

  28. Lin S., Costello D.J. Jr (1983) Error control coding: Fundamentals and applications. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali Gangal.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Çavdar, T., Gangal, A. Application of Sequential Estimation Algorithm Based on Branch Metric to Frequency-Selective Channel Equalization. Wireless Pers Commun 55, 655–664 (2010). https://doi.org/10.1007/s11277-009-9827-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-009-9827-8

Keywords

Navigation