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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:language>eng</dc:language><dc:creator>Ortin, J.</dc:creator><dc:creator>Garcia, P.</dc:creator><dc:creator>Gutierrez, F.</dc:creator><dc:creator>Valdovinos, A.</dc:creator><dc:title>Two Step SOVA-Based Decoding Algorithm for Tailbiting Codes</dc:title><dc:identifier>ART-2009-65812</dc:identifier><dc:description>Abstract—In this work we propose a novel decoding algorithm for tailbiting convolutional codes and evaluate its performance over different channels. The proposed method consists on a fixed two-step Viterbi decoding of the received data. In the first step, an estimation of the most likely state is performed based on a SOVA decoding. The second step consists of a conventional Viterbi decoding that employs the state estimated in the previous step as the initial and final states of the trellis. Simulations results show a performance close to that of maximum-likelihood decoding.</dc:description><dc:date>2009</dc:date><dc:source>http://zaguan.unizar.es/record/149116</dc:source><dc:identifier>http://zaguan.unizar.es/record/149116</dc:identifier><dc:identifier>oai:zaguan.unizar.es:149116</dc:identifier><dc:identifier.citation>IEEE COMMUNICATIONS LETTERS 13, 7 (2009), 510-512</dc:identifier.citation><dc:rights>by</dc:rights><dc:rights>https://creativecommons.org/licenses/by/4.0/deed.es</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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