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Endomorphisms of Linear Block Codes (2402.00562v2)

Published 1 Feb 2024 in cs.IT and math.IT

Abstract: The automorphism groups of various linear codes are extensively studied yielding insights into the respective code structure. This knowledge is used in, e.g., theoretical analysis and in improving decoding performance, motivating the analyses of endomorphisms of linear codes. In this work, we discuss the structure of the set of transformation matrices of code endomorphisms, defined as a generalization of code automorphisms, and provide an explicit construction of a bijective mapping between the image of an endomorphism and its canonical quotient space. Furthermore, we introduce a one-to-one mapping between the set of transformation matrices of endomorphisms and a larger linear block code enabling the use of well-known algorithms for the search for suitable endomorphisms. Additionally, we propose an approach to obtain unknown code endomorphisms based on automorphisms of the code. Furthermore, we consider ensemble decoding as a possible use case for endomorphisms by introducing endomorphism ensemble decoding. Interestingly, EED can improve decoding performance when other ensemble decoding schemes are not applicable.

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References (17)
  1. S. Kudekar, S. Kumar, M. Mondelli, H. D. Pfister, E. Şaşoǧlu, and R. L. Urbanke, “Reed–muller codes achieve capacity on erasure channels,” IEEE Trans. on Inf. Theory, vol. 63, no. 7, pp. 4298–4316, July 2017.
  2. M. Bardet, V. Dragoi, A. Otmani, and J.-P. Tillich, “Algebraic properties of polar codes from a new polynomial formalism,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Barcelona, Spain, 2016.
  3. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “Automorphism ensemble decoding of Reed-Muller codes,” IEEE Trans. Commun., vol. 69, no. 10, pp. 6424–6438, October 2021.
  4. M. Geiselhart, M. Ebada, A. Elkelesh, J. Clausius, and S. ten Brink, “Automorphism ensemble decoding of quasi-cyclic LDPC codes by breaking graph symmetries,” IEEE Commun. Lett., vol. 26, no. 8, pp. 1705–1709, August 2022.
  5. T. Hehn, J. B. Huber, O. Milenkovic, and S. Laendner, “Multiple-bases belief-propagation decoding of high-density cyclic codes,” IEEE Trans. Commun., vol. 58, no. 1, pp. 1–8, January 2010.
  6. T. P. Berger and P. Charpin, “The automorphism groups of BCH codes and of some affine-invariant codes over extension fields,” Des. Codes Cryptogr., vol. 18, no. 1/3, pp. 29–53, December 1999.
  7. M. Geiselhart, A. Elkelesh, M. Ebada, S. Cammerer, and S. ten Brink, “On the automorphism group of polar codes,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Melbourne, Australia, 2021.
  8. J. Mandelbaum, H. Jäkel, and L. Schmalen, “Generalized automorphisms of channel codes: Properties, code design, and a decoder,” in Proc. Int. Symp. on Topics in Coding (ISTC), Brest, France, 2023.
  9. T. Hehn, J. B. Huber, S. Laendner, and O. Milenkovic, “Multiple-bases belief-propagation for decoding of short block codes,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), Nice, France, 2007.
  10. T. Hehn, J. B. Huber, P. He, and S. Laendner, “Multiple-bases belief-propagation with leaking for decoding of moderate-length block codes,” in Proc. Int. ITG Conf. on Source and Channel Coding (SCC), Ulm, Germany, 2008.
  11. M. Geiselhart, J. Clausius, and S. ten Brink, “Rate-compatible polar codes for automorphism ensemble decoding,” in Proc. Int. Symp. on Topics in Coding (ISTC), Brest, France, 2023.
  12. F. Gensheimer, T. Dietz, S. Ruzika, K. Kraft, and N. Wehn, “Improved maximum-likelihood decoding using sparse parity-check matrices,” in Proc. Int. Conf. on Telecommun. (ICT), Saint Malo, France, 2018.
  13. J. Hagenauer, E. Offer, and L. Papke, “Iterative decoding of binary block and convolutional codes,” IEEE Trans. Inf. Theory, vol. 42, no. 2, pp. 429–445, March 1996.
  14. E. Arıkan, “Channel polarization: A method for constructing capacity-achieving codes for symmetric binary-input memoryless channels,” IEEE Trans. Inf. Theory, vol. 55, no. 7, pp. 3051–3073, July 2009.
  15. V. Bioglio, C. Condo, and I. Land, “Design of polar codes in 5G New Radio,” IEEE Commun. Surveys & Tutorials, vol. 23, no. 1, pp. 29–40, January 2021.
  16. M. Helmling, S. Scholl, F. Gensheimer, T. Dietz, K. Kraft, S. Ruzika, and N. Wehn, “Database of Channel Codes and ML Simulation Results,” www.uni-kl.de/channel-codes, 2019, accessed 2023-01-04.
  17. A. Alamdar-Yazdi and F. R. Kschischang, “A simplified successive-cancellation decoder for polar codes,” IEEE Commun. Lett., vol. 15, no. 12, pp. 1378–1380, October 2011.
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