On optimal extended row distance profile
Main Author: | |
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Publication Date: | 2017 |
Other Authors: | , |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10773/17410 |
Summary: | In this paper, we investigate extended row distances of Unit Memory (UM) convolutional codes. In particular, we derive upper and lower bounds for these distances and moreover present a concrete construction of a UM convolutional code that almost achieves the derived upper bounds. The generator matrix of these codes is built by means of a particular class of matrices, called superregular matrices. We actually conjecture that the construction presented is optimal with respect to the extended row distances as it achieves the maximum extended row distances possible. This in particular implies that the upper bound derived is not completely tight. The results presented in this paper further develop the line of research devoted to the distance properties of convolutional codes which has been mainly focused on the notions of free distance and column distance. Some open problems are left for further research. |
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On optimal extended row distance profileConvolutional codesSuperregular matricesUnimemory convolutional codesMaximum Distance Profile (MDP)Maximum Distance Separable (MDS)In this paper, we investigate extended row distances of Unit Memory (UM) convolutional codes. In particular, we derive upper and lower bounds for these distances and moreover present a concrete construction of a UM convolutional code that almost achieves the derived upper bounds. The generator matrix of these codes is built by means of a particular class of matrices, called superregular matrices. We actually conjecture that the construction presented is optimal with respect to the extended row distances as it achieves the maximum extended row distances possible. This in particular implies that the upper bound derived is not completely tight. The results presented in this paper further develop the line of research devoted to the distance properties of convolutional codes which has been mainly focused on the notions of free distance and column distance. Some open problems are left for further research.Springer2017-05-13T15:24:14Z2017-01-04T00:00:00Z2017-01-04book partinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10773/17410eng978-3-319-49982-610.1007/978-3-319-49984-0_4Almeida, P.Napp, D.Pinto, R.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-06T04:01:04Zoai:ria.ua.pt:10773/17410Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T13:54:38.855189Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
On optimal extended row distance profile |
title |
On optimal extended row distance profile |
spellingShingle |
On optimal extended row distance profile Almeida, P. Convolutional codes Superregular matrices Unimemory convolutional codes Maximum Distance Profile (MDP) Maximum Distance Separable (MDS) |
title_short |
On optimal extended row distance profile |
title_full |
On optimal extended row distance profile |
title_fullStr |
On optimal extended row distance profile |
title_full_unstemmed |
On optimal extended row distance profile |
title_sort |
On optimal extended row distance profile |
author |
Almeida, P. |
author_facet |
Almeida, P. Napp, D. Pinto, R. |
author_role |
author |
author2 |
Napp, D. Pinto, R. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Almeida, P. Napp, D. Pinto, R. |
dc.subject.por.fl_str_mv |
Convolutional codes Superregular matrices Unimemory convolutional codes Maximum Distance Profile (MDP) Maximum Distance Separable (MDS) |
topic |
Convolutional codes Superregular matrices Unimemory convolutional codes Maximum Distance Profile (MDP) Maximum Distance Separable (MDS) |
description |
In this paper, we investigate extended row distances of Unit Memory (UM) convolutional codes. In particular, we derive upper and lower bounds for these distances and moreover present a concrete construction of a UM convolutional code that almost achieves the derived upper bounds. The generator matrix of these codes is built by means of a particular class of matrices, called superregular matrices. We actually conjecture that the construction presented is optimal with respect to the extended row distances as it achieves the maximum extended row distances possible. This in particular implies that the upper bound derived is not completely tight. The results presented in this paper further develop the line of research devoted to the distance properties of convolutional codes which has been mainly focused on the notions of free distance and column distance. Some open problems are left for further research. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-05-13T15:24:14Z 2017-01-04T00:00:00Z 2017-01-04 |
dc.type.driver.fl_str_mv |
book part |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/17410 |
url |
http://hdl.handle.net/10773/17410 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
978-3-319-49982-6 10.1007/978-3-319-49984-0_4 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
dc.source.none.fl_str_mv |
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FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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RCAAP |
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RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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