Design of MDP Convolutional Codes and Maximally Recoverable Codes Through the Lens of Matrix Completion

Fuente: arXiv
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Autores principales: Dang, Sakshi, Lieb, Julia, Soto, Pedro, Sprintson, Alex
Formato: Preprint
Publicado: 2026
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author Dang, Sakshi
Lieb, Julia
Soto, Pedro
Sprintson, Alex
author_facet Dang, Sakshi
Lieb, Julia
Soto, Pedro
Sprintson, Alex
contents The matrix completion problem provides a unifying lens through which many fundamental problems in coding theory can be viewed. In this paper, we investigate Locally Recoverable Codes (LRCs) with Maximal Recoverability (MR) and Maximum Distance Profile (MDP) convolutional codes in the framework of matrix completion. In particular, we present techniques that are general enough to provide constructions for both types of codes. A common feature of our code constructions is the sparsity of their generator matrices and the property that a large number of the entries of the generator matrices are elements of a small subfield of a larger extension field.
format Preprint
id arxiv_https___arxiv_org_abs_2604_21544
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Design of MDP Convolutional Codes and Maximally Recoverable Codes Through the Lens of Matrix Completion
Dang, Sakshi
Lieb, Julia
Soto, Pedro
Sprintson, Alex
Information Theory
The matrix completion problem provides a unifying lens through which many fundamental problems in coding theory can be viewed. In this paper, we investigate Locally Recoverable Codes (LRCs) with Maximal Recoverability (MR) and Maximum Distance Profile (MDP) convolutional codes in the framework of matrix completion. In particular, we present techniques that are general enough to provide constructions for both types of codes. A common feature of our code constructions is the sparsity of their generator matrices and the property that a large number of the entries of the generator matrices are elements of a small subfield of a larger extension field.
title Design of MDP Convolutional Codes and Maximally Recoverable Codes Through the Lens of Matrix Completion
topic Information Theory
url https://arxiv.org/abs/2604.21544