English

Limited-Magnitude Error-Correcting Gray Codes for Rank Modulation

Information Theory 2022-08-30 v3 math.IT

Abstract

We construct Gray codes over permutations for the rank-modulation scheme, which are also capable of correcting errors under the infinity-metric. These errors model limited-magnitude or spike errors, for which only single-error-detecting Gray codes are currently known. Surprisingly, the error-correcting codes we construct achieve a better asymptotic rate than that of presently known constructions not having the Gray property, and exceed the Gilbert-Varshamov bound. Additionally, we present efficient ranking and unranking procedures, as well as a decoding procedure that runs in linear time. Finally, we also apply our methods to solve an outstanding issue with error-detecting rank-modulation Gray codes (snake-in-the-box codes) under a different metric, the Kendall τ\tau-metric, in the group of permutations over an even number of elements S2nS_{2n}, where we provide asymptotically optimal codes.

Keywords

Cite

@article{arxiv.1601.05218,
  title  = {Limited-Magnitude Error-Correcting Gray Codes for Rank Modulation},
  author = {Yonatan Yehezkeally and Moshe Schwartz},
  journal= {arXiv preprint arXiv:1601.05218},
  year   = {2022}
}

Comments

Revised version for journal submission. Additional results include more tight auxiliary constructions, a decoding shcema, ranking/unranking procedures, and application to snake-in-the-box codes under the Kendall tau-metric

R2 v1 2026-06-22T12:33:15.431Z