Constructions of MDS convolutional codes using superregular matrices

03/26/2019
by   Julia Lieb, et al.
0

Maximum distance separable convolutional codes are the codes that present best performance in error correction for fixed rate and degree. In this paper we present conditions on the coefficients of the entries of the generator matrices of a convolutional code in order to be maximum distance separable. We also present two novel constructions that fulfill these conditions.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/08/2023

A new construction of an MDS convolutional code of rate 1/2

Maximum distance separable convolutional codes are characterized by the ...
research
08/01/2020

Superregular matrices over small finite fields

A trivially zero minor of a matrix is a minor having all its terms in th...
research
02/19/2020

A note on the explicit constructions of tree codes over polylogarithmic-sized alphabet

Recently, Cohen, Haeupler and Schulman gave an explicit construction of ...
research
02/21/2022

Reducing FEC-Complexity in Cross-Layer Predictable Data Communication

The PRRT protocol enables applications with strict performance requireme...
research
01/03/2021

Matrix constructs

Matrices can be built and designed by applying procedures from lower ord...
research
01/20/2020

Discrete Variational Methods and Symplectic Generalized Additive Runge–Kutta Methods

We consider a Lagrangian system L(q,q̇) = ∑_l=1^NL^{l}(q,q̇), where th...
research
03/14/2022

Multilayer crisscross error and erasure correction

In this work, multilayer crisscross error and erasures are considered, w...

Please sign up or login with your details

Forgot password? Click here to reset