Explicit and Efficient Construction of Nearly Optimal Rate Codes for the Binary Deletion Channel and the Poisson Repeat Channel

Author Ittai Rubinstein



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Ittai Rubinstein
  • Blavatnik School of Computer Science, Tel-Aviv University, Israel
  • QEDMA Quantum Computing, Tel-Aviv, Israel

Acknowledgements

We thank Roni Con, Aviad Rubinstein and Muli Safra for their helpful comments on previous drafts.

Cite As Get BibTex

Ittai Rubinstein. Explicit and Efficient Construction of Nearly Optimal Rate Codes for the Binary Deletion Channel and the Poisson Repeat Channel. In 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 229, pp. 105:1-105:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.ICALP.2022.105

Abstract

Two of the most common models for channels with synchronisation errors are the Binary Deletion Channel with parameter p (BDC_p) - a channel where every bit of the codeword is deleted i.i.d with probability p, and the Poisson Repeat Channel with parameter λ (PRC_λ) - a channel where every bit of the codeword is repeated Poisson(λ) times.
Previous constructions based on synchronisation strings yielded codes with rates far lower than the capacities of these channels [Con and Shpilka, 2019; Guruswami and Li, 2018], and the only efficient construction to achieve capacity on the BDC at the time of writing this paper is based on the far more advanced methods of polar codes [Tal et al., 2021].
In this work, we present a new method for concatenating synchronisation codes and use it to construct simple and efficient encoding and decoding algorithms for both channels with nearly optimal rates.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Coding theory
Keywords
  • Error Correcting Codes
  • Algorithmic Coding Theory
  • Binary Deletion Channel

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References

  1. Stéphane Boucheron, Gábor Lugosi, and Pascal Massart. Concentration inequalities: A nonasymptotic theory of independence. Oxford university press, 2013. Google Scholar
  2. GS Buller and RJ Collins. Single-photon generation and detection. Measurement Science and Technology, 21(1):012002, 2009. Google Scholar
  3. Kuan Cheng, Zhengzhong Jin, Xin Li, and Ke Wu. Deterministic document exchange protocols, and almost optimal binary codes for edit errors. In 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS), pages 200-211. IEEE, 2018. Google Scholar
  4. Mahdi Cheraghchi, Ryan Gabrys, Olgica Milenkovic, and Joao Ribeiro. Coded trace reconstruction. IEEE Transactions on Information Theory, 66(10):6084-6103, 2020. Google Scholar
  5. Mahdi Cheraghchi and João Ribeiro. An overview of capacity results for synchronization channels. IEEE Transactions on Information Theory, 67(6):3207-3232, 2020. Google Scholar
  6. Roni Con and Amir Shpilka. Explicit and efficient constructions of coding schemes for the binary deletion channel and the poisson repeat channel. arXiv preprint, 2019. URL: http://arxiv.org/abs/1909.10177.
  7. Roni Con, Amir Shpilka, and Itzhak Tamo. Linear and reed solomon codes against adversarial insertions and deletions. arXiv preprint, 2021. URL: http://arxiv.org/abs/2107.05699.
  8. Marco Dalai. A new bound on the capacity of the binary deletion channel with high deletion probabilities. In 2011 IEEE International Symposium on Information Theory Proceedings, pages 499-502. IEEE, 2011. Google Scholar
  9. Venkatesan Guruswami and Ray Li. Polynomial time decodable codes for the binary deletion channel. IEEE Transactions on Information Theory, 65(4):2171-2178, 2018. Google Scholar
  10. Venkatesan Guruswami and Carol Wang. Deletion codes in the high-noise and high-rate regimes. IEEE Transactions on Information Theory, 63(4):1961-1970, 2017. Google Scholar
  11. Bernhard Haeupler. Optimal document exchange and new codes for insertions and deletions. In 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS), pages 334-347. IEEE, 2019. Google Scholar
  12. Bernhard Haeupler, Aviad Rubinstein, and Amirbehshad Shahrasbi. Near-linear time insertion-deletion codes and (1+ ε)-approximating edit distance via indexing. In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, pages 697-708, 2019. Google Scholar
  13. Bernhard Haeupler and Amirbehshad Shahrasbi. Synchronization strings: codes for insertions and deletions approaching the singleton bound. In Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, pages 33-46, 2017. Google Scholar
  14. Richard W Hamming. Error detecting and error correcting codes. The Bell system technical journal, 29(2):147-160, 1950. Google Scholar
  15. Adam Kalai, Michael Mitzenmacher, and Madhu Sudan. Tight asymptotic bounds for the deletion channel with small deletion probabilities. In 2010 IEEE International Symposium on Information Theory, pages 997-1001. IEEE, 2010. Google Scholar
  16. Yonglong Li and Vincent YF Tan. On the capacity of channels with deletions and states. IEEE Transactions on Information Theory, 67(5):2663-2679, 2020. Google Scholar
  17. Hugues Mercier, Vijay K Bhargava, and Vahid Tarokh. A survey of error-correcting codes for channels with symbol synchronization errors. IEEE Communications Surveys & Tutorials, 12(1):87-96, 2010. Google Scholar
  18. Michael Mitzenmacher. A survey of results for deletion channels and related synchronization channels. Probability Surveys, 6:1-33, 2009. Google Scholar
  19. Michael Mitzenmacher and Eleni Drinea. A simple lower bound for the capacity of the deletion channel. IEEE Transactions on Information Theory, 52(10):4657-4660, 2006. Google Scholar
  20. Henry D Pfister and Ido Tal. Polar codes for channels with insertions, deletions, and substitutions. In 2021 IEEE International Symposium on Information Theory (ISIT), pages 2554-2559. IEEE, 2021. Google Scholar
  21. Ittai Rubinstein. Explicit and efficient construction of (nearly) optimal rate codes for binary deletion channel and the poisson repeat channel. arXiv preprint, 2021. URL: http://arxiv.org/abs/2111.00261.
  22. Claude Elwood Shannon. A mathematical theory of communication. The Bell system technical journal, 27(3):379-423, 1948. Google Scholar
  23. Ido Tal, Henry D Pfister, Arman Fazeli, and Alexander Vardy. Polar codes for the deletion channel: Weak and strong polarization. IEEE Transactions on Information Theory, 2021. Google Scholar
  24. Scott A Vanstone and Paul C Van Oorschot. An introduction to error correcting codes with applications, volume 71. Springer Science & Business Media, 2013. Google Scholar
  25. Ramji Venkataramanan, Sekhar Tatikonda, and Kannan Ramchandran. Achievable rates for channels with deletions and insertions. IEEE transactions on information theory, 59(11):6990-7013, 2013. Google Scholar
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