{"title":"Coding Methods for String Reconstruction From Erroneous Prefix-Suffix Compositions","authors":"Zitan Chen","doi":"10.1109/JSAIT.2025.3617251","DOIUrl":null,"url":null,"abstract":"The number of zeros and the number of ones in a binary string are referred to as the composition of the string, and the prefix-suffix compositions of a string are a multiset formed by the compositions of the prefixes and suffixes of all possible lengths of the string. In this work, we present binary codes of length <inline-formula> <tex-math>$n$ </tex-math></inline-formula> in which every codeword can be efficiently reconstructed from its erroneous prefix-suffix compositions with at most <inline-formula> <tex-math>$t$ </tex-math></inline-formula> composition errors. All our constructions have decoding complexity polynomial in <inline-formula> <tex-math>$n$ </tex-math></inline-formula> and the best of our constructions has constant rate and can correct <inline-formula> <tex-math>$t=\\Theta (n)$ </tex-math></inline-formula> errors. As a comparison, no prior constructions can afford to efficiently correct <inline-formula> <tex-math>$t=\\Theta (n)$ </tex-math></inline-formula> arbitrary composition errors. Additionally, we propose a method of encoding <inline-formula> <tex-math>$h$ </tex-math></inline-formula> arbitrary strings of the same length so that they can be reconstructed from the multiset union of their error-free prefix-suffix compositions, at the expense of <inline-formula> <tex-math>$h$ </tex-math></inline-formula>-fold coding overhead. In contrast, existing methods can only recover <inline-formula> <tex-math>$h$ </tex-math></inline-formula> distinct strings, albeit with code rate asymptotically equal to <inline-formula> <tex-math>$1/h$ </tex-math></inline-formula>. Building on the top of the proposed method, we also present a coding scheme that enables efficient recovery of <inline-formula> <tex-math>$h$ </tex-math></inline-formula> strings from their erroneous prefix-suffix compositions with <inline-formula> <tex-math>$t=\\Theta (n)$ </tex-math></inline-formula> errors.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"6 ","pages":"394-402"},"PeriodicalIF":2.3000,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE journal on selected areas in information theory","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11192538/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The number of zeros and the number of ones in a binary string are referred to as the composition of the string, and the prefix-suffix compositions of a string are a multiset formed by the compositions of the prefixes and suffixes of all possible lengths of the string. In this work, we present binary codes of length $n$ in which every codeword can be efficiently reconstructed from its erroneous prefix-suffix compositions with at most $t$ composition errors. All our constructions have decoding complexity polynomial in $n$ and the best of our constructions has constant rate and can correct $t=\Theta (n)$ errors. As a comparison, no prior constructions can afford to efficiently correct $t=\Theta (n)$ arbitrary composition errors. Additionally, we propose a method of encoding $h$ arbitrary strings of the same length so that they can be reconstructed from the multiset union of their error-free prefix-suffix compositions, at the expense of $h$ -fold coding overhead. In contrast, existing methods can only recover $h$ distinct strings, albeit with code rate asymptotically equal to $1/h$ . Building on the top of the proposed method, we also present a coding scheme that enables efficient recovery of $h$ strings from their erroneous prefix-suffix compositions with $t=\Theta (n)$ errors.