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FROM MAXIMUM LIKELIHOOD TO ITERATIVE DECODING

Full Paper at IEEE Xplore

Networking and Coding

Přednášející: Pierre Duhamel, Autoři: Florence Alberge, Ziad Naja, University Paris-Sud, France; Pierre Duhamel, CNRS, France

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.

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  Informace o přednášce

Nahráno: 2011-05-26 15:25 - 15:45, Club E
Přidáno: 22. 6. 2011 03:42
Počet zhlédnutí: 33
Rozlišení videa: 1024x576 px, 512x288 px
Délka videa: 0:20:16
Audio stopa: MP3 [6.85 MB], 0:20:16