Efficient Reed-Solomon Iterative Decoder Using Galois Field Instruction Set

  • Daniel Iancu
  • Mayan Moudgill
  • John Glossner
  • Jarmo Takala
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5114)

Abstract

This paper presents a computationally efficient iterative Reed-Solomon (RS) decoder, which is suitable for software implementations on processors with instruction extensions for Galois field multiplication. Simulation models of proposed instructions were included into a processor simulator and performance of RS decoding was analyzed. The method has been validated for both Digital Video Broadcasting (DVB-T/H) and WiMAX and the method provides a total link budget improvement of up to 1 dB.

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References

  1. 1.
    Berlecamp, E.: Bounded distance+1 soft decision Reed-Solomon decoding. IEEE Trans. Inform. Theory 42(3), 704–720 (1996)CrossRefGoogle Scholar
  2. 2.
    Forney, G.D.: Generalized minimum distance decoding. IEEE Trans. Inform. Theory 12(2), 125–131 (1966)MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Taipale, D.J., Pursley, M.: An improvement to generalized minimum distance decoding. IEEE Trans. Inform. Theory 37(1), 167–172 (1991)MATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Wicker, S.B.: Error Control Systems for Digital Communication and Storage. Prentice Hall, Englewood Cliffs (1995)MATHGoogle Scholar
  5. 5.
    Gross, W.J., Kschischang, F.R., Koetter, R., Gulak, P.G.: Towards a VLSI architecture for interpolation-based soft-decoding Reed-Solomon decoders. J. VLSI Sign. Proc. 39(1–2), 93–111 (2005)MATHCrossRefGoogle Scholar
  6. 6.
    Lamarca, M., Sala-Alvarez, J., Martinez, A.: Iterative decoding algorithm for RS-convolutional concatenated codes. In: Proc. 3rd Int. Symp. Turbo Codes and Related Topics, Brest, France, September 1–5, pp. 543–546 (2003)Google Scholar
  7. 7.
    Hagenauer, J., Hoeher, P., Viterbi, A.: Algorithm with soft decision outputs and its applications. In: Proc. IEEE GLOBECOM, Dallas, TX, November 27–30, pp. 1680–1686 (1989)Google Scholar
  8. 8.
    Iancu, D., Ye, H., Glossner, J., Schulte, M., Mamidi, S., Takala, J.: Improved spectral efficiency through iterative concatenated convolutional Reed-Solomon software decoding. In: Proc. Joint IST Workshop Sensor Network & Symp. Trends in Commun., Bratislava, Slovakia, June 24–26, pp. 1–5 (2006)Google Scholar
  9. 9.
    Forney, G.D.: On decoding BCH codes. IEEE Trans. Inform. Theory 11(4), 549–557 (1965)MATHCrossRefMathSciNetGoogle Scholar
  10. 10.
    Wilson, S.G.: Digital Modulation and Coding. Prentice-Hall, Englewood Cliffs (1996)MATHGoogle Scholar
  11. 11.
    Massey, J.L.: Shift register synthesis and BCH decoding. IEEE Trans. Inform. Theory 15(1), 122–127 (1969)MATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Glossner, J., Moudgill, M., Iancu, D., Jintukar, S., Nacer, G., Schulte, M.J.: The Sandblaster SBX 2.0 architecture. In: Proc. Software Defined Radio Technical Conf., Denver, CO, November 5–9 (2007)Google Scholar
  13. 13.
    Mamidi, M., Iancu, D., Iancu, A., Schulte, M.J., Glossner, J.: Instruction set extensions for Reed-Solomon encoding and decoding. In: Proc. IEEE Int. Conf. Application-Specific Syst. Arch. Processors, Samos, Greece, July 23-25, pp. 231–237 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Daniel Iancu
    • 1
  • Mayan Moudgill
    • 1
  • John Glossner
    • 1
  • Jarmo Takala
    • 2
  1. 1.Sandbridge Technologies Inc.USA
  2. 2.Tampere University of TechnologyTampereFinland

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