Decoding Insertions/Deletions via List Recovery
Anisha Banerjee, Roni Con, Antonia Wachter-Zeh, Eitan Yaakobi

TL;DR
This paper introduces a novel approach to decoding insertions and deletions by reducing the problem to list recovery, enabling efficient decoding for Reed-Solomon codes in both adversarial and random insdel models.
Contribution
It presents a new reduction from insdel decoding to list recovery, providing the first efficient insdel decoder for Reed-Solomon codes with k>2, and extends decoding techniques to random insdel channels.
Findings
Efficient insdel decoding for Reed-Solomon codes with k>2.
List recovery approach improves decoding capabilities.
Adaptation of Koetter-Vardy algorithm for insdel errors.
Abstract
In this work, we consider the problem of efficient decoding of codes from insertions and deletions. Most of the known efficient codes are codes with synchronization strings which allow one to reduce the problem of decoding insertions and deletions to that of decoding substitution and erasures. Our new approach, presented in this paper, reduces the problem of decoding insertions and deletions to that of list recovery. Specifically, any \((\rho, 2\rho n + 1, L)\)-list-recoverable code is a \((\rho, L)\)-list decodable insdel code. As an example, we apply this technique to Reed-Solomon (RS) codes, which are known to have efficient list-recovery algorithms up to the Johnson bound. In the adversarial insdel model, this provides efficient (list) decoding from \(t\) insdel errors, assuming that \(t\cdot k = O(n)\). This is the first efficient insdel decoder for \([n, k]\) RS codes for \(k>2\).…
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Taxonomy
TopicsDNA and Biological Computing · semigroups and automata theory · Cryptography and Data Security
