Publication: Column Rank Distances of Rank Metric Convolutional Codes
Column Rank Distances of Rank Metric Convolutional Codes
Date
Date
Date
Citations
Napp, D., Pinto, R., Rosenthal, J., & Santana, F. (2017). Column Rank Distances of Rank Metric Convolutional Codes. In Á. I. Barbero, V. Skachek, & Ø. Ytrehus (Eds.), Coding Theory and Applications: 5th International Castle Meeting on Coding Theory and Applications (No. 10495; Vol. 10495, Issue 10495, pp. 248–256). Springer. https://doi.org/10.1007/978-3-319-66278-7_21
Abstract
Abstract
Abstract
In this paper, we deal with the so-called multi-shot network coding, meaning that the network is used several times (shots) to propagate the information. The framework we present is slightly more general than the one which can be found in the literature. We study and introduce the notion of column rank distance of rank metric convolutional codes for any given rate and finite field. Within this new framework we generalize previous results on column distances of Hamming and rank metric convolutional codes [3, 8]. This contribution can b
Metrics
Views
Additional indexing
Creators (Authors)
- Napp, Diego
- Pinto, Raquel
- Rosenthal, Joachim
- Santana, Filipa
Editors
Title of Book
Title of Book
Title of Book
Place of Publication
Place of Publication
Place of Publication
Page range/Item number
Page range/Item number
Page range/Item number
Page end
Page end
Page end
Item Type
Item Type
Item Type
In collections
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
Series Name
Series Name
Series Name
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
ISBN or e-ISBN
ISBN or e-ISBN
ISBN or e-ISBN
OA Status
OA Status
OA Status
Publisher DOI
Metrics
Views
Citations
Napp, D., Pinto, R., Rosenthal, J., & Santana, F. (2017). Column Rank Distances of Rank Metric Convolutional Codes. In Á. I. Barbero, V. Skachek, & Ø. Ytrehus (Eds.), Coding Theory and Applications: 5th International Castle Meeting on Coding Theory and Applications (No. 10495; Vol. 10495, Issue 10495, pp. 248–256). Springer. https://doi.org/10.1007/978-3-319-66278-7_21