Strongly-MDS convolutional codes

Heide Gluesing-Luerssen, Joachim Rosenthal, Roxana Smarandache

Research output: Contribution to journalArticlepeer-review

109 Scopus citations

Abstract

Maximum-distance separable (MDS) convolutional codes have the property that their free distance is maximal among all codes of the same rate and the same degree. In this paper, a class of MDS convolutional codes is introduced whose column distances reach the generalized Singleton bound at the earliest possible instant. Such codes are called strongly-MDS convolutional codes. They also have a maximum or near-maximum distance profile. The extended row distances of these codes will also be discussed briefly.

Original languageEnglish
Pages (from-to)584-598
Number of pages15
JournalIEEE Transactions on Information Theory
Volume52
Issue number2
DOIs
StatePublished - Feb 2006

Bibliographical note

Funding Information:
Manuscript received March 20, 2003; revised October 14, 2005. This work was supported in part by the Nationa Science Foundation under Grants DMS-0072383 and CCR-0205310. The material in this paper was presented at the 2002 IEEE International Symposium on Information Theory, Lausanne, Switzerland, June/July 2002 and at the International Symposium on the Mathematical Theory of Networks and Systems (MTNS), University of Notre Dame, Notre Dame, IN, August 2002.

Keywords

  • Column distances
  • Convolutional codes
  • Extended row distances
  • Maximum-distance separable (MDS) codes
  • Super-regular matrices
  • Unit memory codes

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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