A-posteriori Probability Decoding of Variable-Length Codes Using a Three-Dimensional Trellis Representation

Jörg Kliewer, Ragnar Thobaben

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations


In this contribution we present an improved index-based a-posteriori probability (APP) decoding approach for variable-length encoded packetized data, where implicit residual source correlation is exploited for error protection. The proposed algorithm is based on a novel generalized two-dimensional state representation which leads to a three-dimensional trellis with unique state transitions. APP decoding on this trellis is realized by employing a two-dimensional version of the classical BCJR algorithm. This new method has the advantage that due to the unique state representation all available a-priori information can be fully exploited, which especially holds for the transition probabilities of the Markov model associated with the variable-length encoded source indices. Simulation results for an additional error protection by channel codes and iterative joint source-channel decoding show that the proposed approach leads to an increased error-correction performance compared to previously published results where a one-dimensional state representation is used.

Original languageEnglish (US)
Number of pages5
StatePublished - 2003
Externally publishedYes
EventIEEE Global Telecommunications Conference GLOBECOM'03 - San Francisco, CA, United States
Duration: Dec 1 2003Dec 5 2003


OtherIEEE Global Telecommunications Conference GLOBECOM'03
Country/TerritoryUnited States
CitySan Francisco, CA

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Global and Planetary Change


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