Threshold Rates for Properties of Random Codes

Venkatesan Guruswami, Jonathan Mosheiff, Nicolas Resch, Shashwat Silas, Mary Wootters

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Suppose that P is a property that may be satisfied by a random code C⊂Σn . For example, for some p∈(0,1) , P might be the property that there exist three elements of C that lie in some Hamming ball of radius pn . We say that R is the threshold rate for P if a random code of rate R∗+ε is very likely to satisfy P , while a random code of rate R−ε is very unlikely to satisfy P . While random codes are well-studied in coding theory, even the threshold rates for relatively simple properties like the one above are not well understood. We characterize threshold rates for a rich class of properties. These properties, like the example above, are defined by the inclusion of specific sets of codewords which are also suitably “symmetric.” For properties in this class, we show that the threshold rate is in fact equal to the lower bound that a simple first-moment calculation obtains. Our techniques not only pin down the threshold rate for the property P above, they give sharp bounds on the threshold rate for list-recovery in several parameter regimes, as well as an efficient algorithm for estimating the threshold rates for list-recovery in general.
Original languageEnglish
Article number9590564
Pages (from-to)905-922
Number of pages18
JournalIEEE Transactions on Information Theory
Volume68
Issue number2
DOIs
StatePublished - 27 Oct 2021
Externally publishedYes

Keywords

  • Codes
  • Decoding
  • Linear codes
  • Computer science
  • Pins
  • Technological innovation
  • Probabilistic logic

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