Error correction for differential linear network coding in slowly-varying networks

Sven Puchinger, Michael Cyran, Robert F.H. Fischer, Martin Bossert, Johannes B. Huber

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Differential linear network coding (DLNC) is a precoding scheme for information transmission over random linear networks. By using differential encoding and decoding, the conventional approach of lifting, required for inherent channel sounding, can be omitted and in turn higher transmission rates are supported. However, the scheme is sensitive to variations in the network topology. In this paper, we derive an extended DLNC channel model which includes slow network changes. Based on this, we propose and analyze a suitable channel coding scheme matched to the situation at hand using rank-metric convolutional codes.

Original languageEnglish
Title of host publicationSCC 2015 - 10th International ITG Conference on Systems, Communications and Coding
PublisherVDE VERLAG GMBH
ISBN (Electronic)9783800736591
StatePublished - 2019
Externally publishedYes
Event10th International ITG Conference on Systems, Communications and Coding, SCC 2015 - Hamburg, Germany
Duration: 2 Feb 20155 Feb 2015

Publication series

NameSCC 2015 - 10th International ITG Conference on Systems, Communications and Coding

Conference

Conference10th International ITG Conference on Systems, Communications and Coding, SCC 2015
Country/TerritoryGermany
CityHamburg
Period2/02/155/02/15

Keywords

  • Differential linear network coding
  • Partial-unit-memory codes
  • Random linear network coding
  • Rank-metric codes

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