Syndrome Compression for Optimal Redundancy Codes

Abstract

We introduce a general technique that we call syndrome compression, for designing low-redundancy error correcting codes. The technique allows us to boost the redundancy efficiency of hash/labeling-based codes by further compressing the labeling. We apply syndrome compression to different types of adversarial deletion channels and present code constructions that correct up to a constant number of errors. Our code constructions achieve the redundancy of twice the Gilbert-Varshamov bound, which improve upon the state of art for these channels. The encoding/decoding complexity of our constructions is of order equal to the size of the corresponding deletion balls, namely, it is polynomial in the code length.

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