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Faster decoding of rank metric convolutional codes


Napp, Diego; Pinto, Raquel; Rosenthal, Joachim; Vettori, Paolo (2018). Faster decoding of rank metric convolutional codes. In: 23rd International Symposium on Mathematical Theory of Networks and Systems, Hong Kong, 16 July 2018 - 20 July 2018, 507-510.

Abstract

A new construction of maximum rank distance systematic rank metric convolutional codes is presented, which permits to reduce the computational complexity of the decoding procedure, i.e., of the underlying Viterbi algorithm. This result is achieved by lowering the number of branch metrics to be calculated and by setting to the highest value the metric of the remaining edges in the trellis.

Abstract

A new construction of maximum rank distance systematic rank metric convolutional codes is presented, which permits to reduce the computational complexity of the decoding procedure, i.e., of the underlying Viterbi algorithm. This result is achieved by lowering the number of branch metrics to be calculated and by setting to the highest value the metric of the remaining edges in the trellis.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:510 Mathematics
Language:English
Event End Date:20 July 2018
Deposited On:13 Feb 2019 10:23
Last Modified:25 Sep 2019 00:25
Additional Information:Hong Kong University of Science and Technology, Hong Kong, July 16-20, 2018
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:http://mtns2018.ust.hk/media/files/0071.pdf
Related URLs:http://mtns2018.ust.hk/proceedings_online.html (Publisher)
Project Information:
  • : FunderSNSF
  • : Grant ID200020_169510
  • : Project TitleAlgebraic Constructions and Decoding of Rank Metric Codes with Applications to Network Coding and Code based Cryptography

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