From Maximum Likelihood to Iterative Decoding - CentraleSupélec Access content directly
Conference Papers Year : 2011

From Maximum Likelihood to Iterative Decoding

Abstract

Iterative decoding is considered in this paper from an optimization point of view. Starting from the optimal maximum likelihood decoding, a (tractable) approximate criterion is derived. The global maximum of the approximate criterion is analyzed: the maximum likelihood solution can be retrieved from the approximate criterion in some particular cases. The classical equations of turbo-decoders can be obtained as an instance of an hybrid Jacobi/Gauss-Seidel implementation of the iterative maximization for the tractable criterion. The extrinsics are a natural consequence of this implementation. In the simulation part, we show a practical application of these results.
Fichier principal
Vignette du fichier
Icassp11_MaxVraisDecIt.pdf (106.22 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00617262 , version 1 (26-08-2011)

Identifiers

Cite

Florence Alberge, Ziad Naja, Pierre Duhamel. From Maximum Likelihood to Iterative Decoding. ICASSP 2011 - 36th IEEE International Conference on Acoustics, Speech and Signal Processing, May 2011, Prague, Czech Republic. pp.3052-3055, ⟨10.1109/ICASSP.2011.5946302⟩. ⟨hal-00617262⟩
71 View
215 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More