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The rank decoding problem has been the subject of much attention in this last decade. This problem, which is at the base of the security of public-key cryptosystems based on rank metric codes, is traditionally studied over finite fields.…

Information Theory · Computer Science 2022-08-16 Hervé Tale Kalachi , Hermann Tchatchiem Kamche

This paper establishes information-theoretic limits in estimating a finite field low-rank matrix given random linear measurements of it. These linear measurements are obtained by taking inner products of the low-rank matrix with random…

Information Theory · Computer Science 2015-03-19 Vincent Y. F. Tan , Laura Balzano , Stark C. Draper

The problem of error control in random linear network coding is addressed from a matrix perspective that is closely related to the subspace perspective of K\"otter and Kschischang. A large class of constant-dimension subspace codes is…

Information Theory · Computer Science 2019-05-07 Danilo Silva , Frank R. Kschischang , Ralf Kötter

In the recent years, the notion of rank metric in the context of coding theory has known many interesting developments in terms of applications such as space time coding, network coding or public key cryptography. These applications raised…

Information Theory · Computer Science 2021-06-11 Alain Couvreur , Thomas Debris-Alazard , Philippe Gaborit

We present the theory of linear rank-metric codes from the point of view of their fundamental parameters. These are: the minimum rank distance, the rank distribution, the maximum rank, the covering radius, and the field size. The focus of…

Information Theory · Computer Science 2023-12-12 Anina Gruica , Altan B. Kilic , Alberto Ravagnani

Rank-metric codes are subspaces of matrices over finite fields endowed with the rank metric and admit a natural tensorial representation. The tensor rank provides a measure of the minimal size of a decomposition of a code into rank-one…

Information Theory · Computer Science 2026-05-22 Matteo Bonini , Eimear Byrne , Giuseppe Cotardo

The rank metric measures the distance between two matrices by the rank of their difference. Codes designed for the rank metric have attracted considerable attention in recent years, reinforced by network coding and further motivated by a…

Information Theory · Computer Science 2022-03-24 Hannes Bartz , Lukas Holzbaur , Hedongliang Liu , Sven Puchinger , Julian Renner , Antonia Wachter-Zeh

In this paper, we propose and study $r$-minimal codes, a natural extension of minimal codes which have been extensively studied with respect to Hamming metric, rank metric and sum-rank metric. We first propose $r$-minimal codes in a general…

Information Theory · Computer Science 2024-08-29 Yang Xu , Haibin Kan , Guangyue Han

In this paper we introduce and investigate rank-metric intersecting codes, a new class of linear codes in the rank-metric context, inspired by the well-studied notion of intersecting codes in the Hamming metric. A rank-metric code is said…

Combinatorics · Mathematics 2025-07-02 Daniele Bartoli , Martino Borello , Giuseppe Marino , Martin Scotti

In this paper, we study the hardness of decoding a random code endowed with the cover metric. As the cover metric lies in between the Hamming and rank metric, it presents itself as a promising candidate for code-based cryptography. We give…

Information Theory · Computer Science 2022-05-26 Sebastian Bitzer , Julian Renner , Antonia Wachter-Zeh , Violetta Weger

The minimum distance is one of the most important combinatorial characterizations of a code. The maximum likelihood decoding problem is one of the most important algorithmic problems of a code. While these problems are known to be hard for…

Information Theory · Computer Science 2016-08-31 Qi Cheng

In this paper, we first introduce the concept of elementary linear subspace, which has similar properties to those of a set of coordinates. We then use elementary linear subspaces to derive properties of maximum rank distance (MRD) codes…

Information Theory · Computer Science 2008-03-03 Maximilien Gadouleau , Zhiyuan Yan

We examine LDPC codes decoded using linear programming (LP). Four contributions to the LP framework are presented. First, a new method of tightening the LP relaxation, and thus improving the LP decoder, is proposed. Second, we present an…

Information Theory · Computer Science 2016-11-17 David Burshtein , Idan Goldenberg

In this paper we study the hardness of the syndrome decoding problem over finite rings endowed with the Lee metric. We first prove that the decisional version of the problem is NP-complete, by a reduction from the $3$-dimensional matching…

Information Theory · Computer Science 2022-04-04 Violetta Weger , Karan Khathuria , Anna-Lena Horlemann , Massimo Battaglioni , Paolo Santini , Edoardo Persichetti

This paper presents encoding and decoding algorithms for several families of optimal rank metric codes whose codes are in restricted forms of symmetric, alternating and Hermitian matrices. First, we show the evaluation encoding is the right…

Information Theory · Computer Science 2022-02-08 Wrya K. Kadir , Chunlei Li , Ferdinando Zullo

Sum-rank Hamming codes are introduced in this work. They are essentially defined as the longest codes (thus of highest information rate) with minimum sum-rank distance at least $ 3 $ (thus one-error-correcting) for a fixed redundancy $ r $,…

Information Theory · Computer Science 2021-01-13 Umberto Martínez-Peñas

In this paper we consider general rank minimization problems with rank appearing in either objective function or constraint. We first establish that a class of special rank minimization problems has closed-form solutions. Using this result,…

Optimization and Control · Mathematics 2012-05-30 Zhaosong Lu , Yong Zhang

This paper presents an algorithm for decoding homogeneous interleaved codes of high interleaving order in the rank metric. The new decoder is an adaption of the Hamming-metric decoder by Metzner and Kapturowski (1990) and guarantees to…

Information Theory · Computer Science 2019-04-19 Sven Puchinger , Julian Renner , Antonia Wachter-Zeh

The sum-rank metric provides a unifying framework that generalizes both the celebrated Hamming and rank metrics, and has found applications in areas such as network coding, distributed storage, and space-time coding. A central problem is to…

Information Theory · Computer Science 2026-05-01 Aida Abiad , Antonina P. Khramova , Sven C. Polak , Ferdinando Zullo

We extend the notion of locality from the Hamming metric to the rank and subspace metrics. Our main contribution is to construct a class of array codes with locality constraints in the rank metric. Our motivation for constructing such codes…

Information Theory · Computer Science 2019-05-07 Swanand Kadhe , Salim El Rouayheb , Iwan Duursma , Alex Sprintson
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