Decoding of Convolutional Codes Using a Syndrome Trellis

V. Sidorenko, V. Zyablov

Research output: Contribution to journalArticlepeer-review

55 Citations (Scopus)

Abstract

Soft-decision maximum-likelihood decoding of convolutional codes using the Viterbi algorithm with a syndrome trellis is proposed. The parity check matrix of a convolutional code is used to construct the trellis. This trellis is minimal. The number of operations for the decoding of one block of a q-ary rate k/n convolutional code is ~ngmin(k'n-k)qv, where v is the memory size of the code. When the code rate satisfies k / n > ½, the proposed algorithm is simpler than the classical Viterbi algorithm that has complexity ~nqkq v.

Original languageEnglish
Pages (from-to)1663-1666
Number of pages4
JournalIEEE Transactions on Information Theory
Volume40
Issue number5
DOIs
Publication statusPublished - Sep 1994
Externally publishedYes

Keywords

  • complexity estimation
  • Convolutional codes
  • maximum-likelihood decoding
  • trellis decoding

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