Error correction based on partial information

Itzhak Tamo, Min Ye, Alexander Barg

Research output: Contribution to journalArticlepeer-review


We consider the decoding of linear and array codes from errors when we are only allowed to download a part of the codeword. More specifically, suppose that we have encoded k data symbols using an (n,k) code with code length n and dimension k. During storage, some of the codeword coordinates might be corrupted by errors. We aim to recover the original data by reading the corrupted codeword with a limit on the transmission bandwidth, namely, we can only download an \alpha proportion of the corrupted codeword. For a given \alpha , our objective is to design a code and a decoding scheme such that we can recover the original data from the largest possible number of errors. A naive scheme is to read \alpha n coordinates of the codeword. This method used in conjunction with MDS codes guarantees recovery from any \lfloor (\alpha n-k)/2\rfloor errors. In this paper we show that we can instead download an \alpha proportion from each of the codeword's coordinates. For a well-designed MDS code, this method can guarantee recovery from \lfloor (n-k/\alpha)/2 \rfloor errors, which is 1/\alpha times more than the naive method, and is also the maximum number of errors that an (n,k) code can correct by downloading only an \alpha proportion of the codeword. We present two families of such optimal constructions and decoding schemes of which one is based on Interleaved Reed-Solomon codes and the other on Folded Reed-Solomon codes. We further show that both code constructions attain asymptotically optimal list decoding radius when downloading only a part of the corrupted codeword. We also construct an ensemble of random codes that with high probability approaches the upper bound on the number of correctable errors when the decoder downloads an \alpha proportion of the corrupted codeword.

Original languageEnglish
Article number8906047
Pages (from-to)1396-1404
Number of pages9
JournalIEEE Transactions on Information Theory
Issue number3
StatePublished - Mar 2020


  • Distributed storage
  • MDS codes
  • Reed-Solomon codes
  • random coding
  • α-decoding radius

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences


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