English

Embedding linear codes into self-orthogonal codes and their optimal minimum distances

Information Theory 2021-03-16 v2 math.IT

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 kk-dimensional linear code C\mathcal{C} (k=2,3,4k = 2,3,4) into a self-orthogonal code of the shortest length which has the same dimension kk and minimum distance dd(C)d' \ge d(\mathcal{C}). For k>4k > 4, we suggest a recursive method to embed a kk-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 nn with dimension 4 and any length n≢6,13,14,21,22,28,29(mod31)n \not\equiv 6,13,14,21,22,28,29 \pmod{31} with dimension 5. We determine the exact optimal minimum distances of [n,4][n,4] self-orthogonal codes which were left open by Li-Xu-Zhao (2008) when n0,3,4,5,10,11,12(mod15)n \equiv 0,3,4,5,10,11,12 \pmod{15}. Then, using MAGMA, we observe that our embedding sends an optimal linear code to an optimal self-orthogonal code.

Keywords

Cite

@article{arxiv.2002.01643,
  title  = {Embedding linear codes into self-orthogonal codes and their optimal minimum distances},
  author = {Jon-Lark Kim and Young-Hun Kim and Nari Lee},
  journal= {arXiv preprint arXiv:2002.01643},
  year   = {2021}
}

Comments

19 pages; to appear in IEEE Trans. Inform. Theory

R2 v1 2026-06-23T13:31:35.191Z