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Coding on a trellis: Convolutional codes

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Coding for Wireless Channels
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Abstract

In the previous chapter we have seen how a given block code can be represented by using a trellis. We now examine the problem of designing a binary code directly on a trellis. This can be done by first choosing a trellis with a preassigned complexity, then labeling its brunches. The trellis is generated by using one or more binary shift registers. The choice of a periodic trellis, which simplifies the Viterbi algorithm, and of symbols generated as linear combinations of the contents of the shift registers, leads to the definition of convolutional codes. Invented in 1954. these codes have been very successful because they can be decoded in a simple way. have a good performance, and are well adapted to the transmission of continuous streams of data. In this chapter, we present the rudiments of an algebraic theory of convolutional codes, and show how code performance can be evaluated.

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References

  1. S. Benedetto and E. Biglieri, Digital Transmission Principles with Wireless Applications. New York: Kluwer/Plenum, 1999.

    Google Scholar 

  2. J. B. Cain, G. C. Clark, Jr., and J. M. Geist, “Punctured convolutional codes of rate (n − 1)/n and simplified maximum likelihood decoding,” IEEE Trans. Inform. Theory, Vol. 25, No. 1, pp. 97–100, January 1979.

    Article  MathSciNet  Google Scholar 

  3. J.-J. Chang, D.-J. Hwang, and M.-C. Lin, “Some extended results on the search for good convolutional codes,” IEEE Trans. Inform. Theory, Vol. 43, No. 5, pp. 1682–1697, September 1997.

    Article  MATH  MathSciNet  Google Scholar 

  4. G. D. Forney, Jr., “Convolutional codes. I: Algebraic structure,” IEEE Trans. Inform. Theory, Vol. IT-16, No. 6, pp. 720–738, November 1970.

    Article  MathSciNet  Google Scholar 

  5. J. Hagenauer, “Rate-compatible punctured convolutional codes (RCPC codes) and their applications,” IEEE Trans. Commun., Vol. 36, No. 4, pp. 389–400, April 1988.

    Article  Google Scholar 

  6. C. Heegard and S. B. Wicker, Turbo Coding. Boston, MA: Kluwer Academic, 1999.

    Google Scholar 

  7. R. Johannesson and Z.-X. Wan, “A linear algebra approach to minimal convolutional encoders,” IEEE Trans. Inform. Theory, Vol. 39, No. 4, pp. 1219–1233, July 1993.

    Article  MATH  MathSciNet  Google Scholar 

  8. R. Johannesson and K. Sh. Zigangirov, Fundamentals of Convolutional Coding. Piscataway, NJ: IEEE Press, 1999.

    Google Scholar 

  9. R. Knopp, Coding and Multiple Access over Fading Channels, Ph.D. Thesis, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland, 1997.

    Google Scholar 

  10. K. J. Larsen, “Short convolutional codes with maximal free distance for rates 1/2, 1/3 and 1/4,” IEEE Trans. Inform. Theory, Vol. 19, No. 3, pp. 371–372, May 1973.

    Article  MATH  Google Scholar 

  11. H. H. Ma and J. K. Wolf, “On tail biting convolutional codes,” IEEE Trans. Commun., Vol. 34, No. 2, pp. 104–111, February 1986.

    Article  MATH  Google Scholar 

  12. H. Moon, “Improved upper bound on bit error probability for truncated convolutional codes,” IEE Electronics Letters, Vol. 34, No. 1, pp. 65–66, 8th January 1998.

    Article  Google Scholar 

  13. A. J. Viterbi and J. K. Omura, Principles of Digital Communication and Coding. New York: McGraw-Hill, 1979.

    Google Scholar 

  14. Y. Yasuda, K. Kashiki, and Y. Hirata, “High-rate punctured convolutional codes for soft-decision Viterbi decoding,” IEEE Trans. Commun., Vol. 32, No. 3, pp. 315–319, March 1984.

    Article  Google Scholar 

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© 2005 Springer Science+Business Media, Inc.

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(2005). Coding on a trellis: Convolutional codes. In: Coding for Wireless Channels. Information Technology: Transmission, Processing and Storage. Springer, Boston, MA. https://doi.org/10.1007/1-4020-8084-0_6

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  • DOI: https://doi.org/10.1007/1-4020-8084-0_6

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-8083-8

  • Online ISBN: 978-1-4020-8084-5

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