From maximum likelihood to iterative decoding

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.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Florence Alberge, Ziad Naja, Pierre Duhamel
• Keywords: Approximate Criterion, ICASSP 2011, Maximum Likelihood, Optimal Maximum Likelihood, Signal Processing