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Column Distances of Convolutional Codes Over ${\mathbb Z}_{p^r}$.

Authors :
Napp, Diego
Pinto, Raquel
Toste, Marisa
Source :
IEEE Transactions on Information Theory. Feb2019, Vol. 65 Issue 2, p1063-1071. 9p.
Publication Year :
2019

Abstract

Maximum distance profile codes over finite non-binary fields have been introduced and thoroughly studied in the last decade. These codes have the property that their column distances are maximal among all codes of the same rate and degree. In this paper, we aim at studying this fundamental concept in the context of convolutional codes over a finite ring. We extensively use the concept of $p$ -encoder to establish the theoretical framework and derive several bounds on the column distances. In particular, a method for constructing (not necessarily free) maximum distance profile convolutional codes over ${\mathbb Z}_{p^{r}}$ is presented. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189448
Volume :
65
Issue :
2
Database :
Academic Search Index
Journal :
IEEE Transactions on Information Theory
Publication Type :
Academic Journal
Accession number :
134231221
Full Text :
https://doi.org/10.1109/TIT.2018.2870436