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Absorbing sets of codes from finite geometries

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Abstract

We examine the presence of absorbing sets, fully absorbing sets, and elementary absorbing sets in low-density parity-check (LDPC) codes arising from certain classes of finite geometries. In particular, we prove the parameters of the smallest absorbing sets for finite geometry codes using a tree-based argument. Moreover, we obtain the parameters of the smallest absorbing sets for a special class of codes whose graphs are d-left-regular with girth g = 6 or g = 8.

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References

  1. Haymaker, K.: Absorbing set analysis of codes from affine planes. In: Barbero, Á. I., Skachek, V., Ytrehus, Ø. (eds.) International Castle Meeting on Coding Theory and Applications 2017, Lecture Notes in Computer Science 10495, pp. 154–162. Springer, Cham (2017)

  2. Kou, Y., Lin, S., Fossorier, M.: Construction of low density parity check codes: a geometric approach. In: Proceedings of the 2nd IEEE International Symposium on Turbo Codes and Related Topics, pp. 137–140 (2000)

  3. Kou, Y., Lin, S., Fossorier, M.: Low-density parity-check codes based on finite geometries: a rediscovery and new results. IEEE Trans. Inf. Theory 47(7), 2711–2736 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  4. Kelley, C.A., Sridhara, D., Rosenthal, J.: Tree-based construction of LDPC codes having good pseudocodeword weights. IEEE Trans. Inf. Theory 53(4), 1460–1478 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  5. Xia, S.T., Fu, F.W.: On the stopping distance of finite geometry LDPC codes. IEEE Commun. Lett. 10(5), 381–383 (2006)

    Article  Google Scholar 

  6. Smarandache, R., Vontobel, P. O.: Pseudo-codeword analysis of Tanner graphs from projective and Euclidean planes. IEEE Trans. Inf. Theory 53(7), 2376–2393 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  7. Landner, S., Milenkovic, O.: Algorithmic and combinatorial analysis of trapping sets in structured LDPC codes. In: Proceedings of the IEEE Wireless Networks Communications and Mobile Computing, pp. 630–635 (2005)

  8. Diao, Q., Tai, Y.Y., Lin, S., Abdel-Ghaffar, K.: Trapping set structure of LDPC codes on finite geometries. In: Proceedings of the IEEE Information Theory and Applications Workshop (ITA), pp. 1–8 (2013)

  9. Liu, H., Li, Y., Ma, L., Chen, J.: On the smallest absorbing sets of LDPC codes from finite planes. IEEE Trans. Inf. Theory 58(6), 4014–4020 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  10. Koetter, R., Vontobel, P.O.: Graph covers and iterative decoding of finite-length codes. In: Proceedings of the 3rd International Symposium on Turbo Codes and Related Topics, Brest, France, pp. 75–82 (2003)

  11. Dolecek, L., Zhang, Z., Anantharam, V., Wainwright, M., Nikolic, B.: Analysis of absorbing sets for array-based LDPC codes. In: Proceedings of the IEEE International Conference on Communications, pp. 6261–6268 (2007)

  12. Richardson, T.: Error floors of LDPC codes. In: Proceedings of the Annual Allerton Conference on Communications Control, and Computing, vol. 41, pp. 1426–1435 (2003)

  13. Di, C., Proietti, D., Telatar, I.E., Richardson, T.J., Urbanke, R.L.: Finite-length analysis of low-density parity-check codes on the binary erasure channel. IEEE Trans. Inf. Theory 48(6), 1570–1579 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  14. Dolecek, L., Lee, P., Zhang, Z., Anantharam, V., Nikolic, B., Wainwright, M.: Predicting error floors of structured LDPC codes: deterministic bounds and estimates. IEEE J. Sel. Areas Commun. 27(6), 908–917 (2009)

    Article  Google Scholar 

  15. Zhang, S., Schlegel, C.: Controlling the error floor in LDPC decoding. IEEE Trans. Commun. 61(9), 3566–3575 (2013)

    Article  Google Scholar 

  16. Hatami, H., Mitchell, D.G.M., Costello, D.J., Fuja, T.: Performance bounds for quantized LDPC decoders based on absorbing sets. In: Proceedings of the IEEE International Symposium on Information Theory, Barcelona, Spain, pp. 2539–2543 (2016)

  17. Tanner, R. M.: A recursive approach to low-complexity codes. IEEE Trans. Inf. Theory 27(5), 533–547 (1981)

    Article  MathSciNet  MATH  Google Scholar 

  18. Dolecek, L.: On absorbing sets of structured sparse graph codes. In: Proceedings of the IEEE Information Theory and Applications Workshop (ITA), pp. 1–5 (2010)

  19. Schwartz, M., Vardy, A.: On the stopping distance and the stopping redundancy of codes. IEEE Trans. Inf. Theory 52(3), 922–932 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  20. Feldman, J., Wainwright, M.J., Karger, D.R.: Using linear programming to decode binary linear codes. IEEE Trans. Inf. Theory 51(3), 954–972 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  21. Batten, L. M.: Combinatorics of Finite Geometries, 2nd edn. Cambridge University Press, Cambridge (1997)

  22. Tang, H., Xu, J., Lin, S., Abdel-Ghaffar, K.A.S.: Codes on finite geometries. IEEE Trans. Inf. Theory 51(2), 572–596 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  23. Amiri, B., Lin, C.W., Dolecek, L.: Asymptotic distribution of absorbing sets and fully absorbing sets for regular sparse code ensembles. IEEE Trans. Commun. 61 (2), 455–464 (2013)

    Article  Google Scholar 

  24. Kyung, G.B., Wang, C.C.: Finding the exhaustive list of small fully absorbing sets and designing the corresponding low error-floor decoder. IEEE Trans. Commun. 60(6), 1487–1498 (2012)

    Article  Google Scholar 

  25. Johnson, S.J., Weller, S.R.: Codes for iterative decoding from partial geometries. IEEE Trans. Commun. 52(2), 236–243 (2004)

    Article  Google Scholar 

  26. Tanner, R.M.: Explicit concentrators from generalized N-gons. SIAM J. Algebr. Discret. Methods 5(3), 287–293 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  27. Hirschfeld, J.W., Storme, L.: The packing problem in statistics, coding theory and finite projective spaces: update 2001. In: Finite Geometries, pp. 201–246. Springer, Boston (2001)

  28. Ball, S.: Finite Geometry and Combinatorial Applications. London Mathematical Society Student Texts Vol. 82. Cambridge University Press, Cambridge (2015)

    Book  Google Scholar 

  29. Bierbrauer, J., Edel, Y.: Large caps in projective Galois spaces. In: De Beule, M., Storme, L (eds.) Current Research Topics in Galois Geometry, pp. 85–102. Nova Science Publishers (2011)

  30. Beemer, A., Habib, S., Kelley, C.A., Kliewer, J.: A generalized algebraic approach to optimizing SC-LDPC codes. In: Proceedings of the Annual Allerton Conference on Communication Control, and Computing, vol. 55, pp. 672–679 (2017)

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Acknowledgements

K. Haymaker would like to thank Pascal Vontobel for noting an error in Lemma 2 of [1], which was helpful in the preparation of this paper.

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Beemer, A., Haymaker, K. & Kelley, C.A. Absorbing sets of codes from finite geometries. Cryptogr. Commun. 11, 1115–1131 (2019). https://doi.org/10.1007/s12095-019-0353-6

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