MATEC Web of Conferences (Jan 2017)

Divergence coding for convolutional codes

  • Valery Zolotarev,
  • Gennady Ovechkin,
  • Dina Satybaldina,
  • Nurlan Tashatov,
  • Eldor Egamberdiyev

DOI
https://doi.org/10.1051/matecconf/201712505009
Journal volume & issue
Vol. 125
p. 05009

Abstract

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In the paper we propose a new coding/decoding on the divergence principle. A new divergent multithreshold decoder (MTD) for convolutional self-orthogonal codes contains two threshold elements. The second threshold element decodes the code with the code distance one greater than for the first threshold element. Errorcorrecting possibility of the new MTD modification have been higher than traditional MTD. Simulation results show that the performance of the divergent schemes allow to approach area of its effective work to channel capacity approximately on 0,5 dB. Note that we include the enough effective Viterbi decoder instead of the first threshold element, the divergence principle can reach more. Index Terms — error-correcting coding, convolutional code, decoder, multithreshold decoder, Viterbi algorithm.