Litcius/Paper detail

Embedding Linear Codes Into Self-Orthogonal Codes and Their Optimal Minimum Distances

Jon-Lark Kim, Young-Hun Kim, Nari Lee

2021IEEE Transactions on Information Theory26 citationsDOI

Abstract

We obtain a characterization on self-orthogonality for a given binary linear code in terms of the number of column vectors in its generator matrix, which extends the result of Bouyukliev et al. (2006). As an application, we give an algorithmic method to embed a given binary k-dimensional linear code <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</i> ( k = 3,4) into a self-orthogonal code of the shortest length which has the same dimension k and minimum distance d' ≥ d( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</i> ). For k > 4, we suggest a recursive method to embed a k-dimensional linear code to a self-orthogonal code. We also give new explicit formulas for the minimum distances of optimal self-orthogonal codes for any length n with dimension 4 and any length n \not ≡ 6, 13,14,21,22,28,29 (mod 31) with dimension 5.

Topics & Concepts

Dimension (graph theory)CombinatoricsCode (set theory)MathematicsDiscrete mathematicsLinear codeOrthogonalityGenerator matrixMinimum distanceBinary numberBinary codeMatrix (chemical analysis)EmbeddingAlgorithmDecoding methodsBlock codeComputer scienceArithmeticSet (abstract data type)Composite materialMaterials scienceArtificial intelligenceGeometryProgramming languageCoding theory and cryptographyError Correcting Code TechniquesCooperative Communication and Network Coding