Divergence coding for convolutional codes

MATEC Web of Conferences, 2017

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1051/matecconf/201712505009
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

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.