Improved Max-Log-MAP Turbo Decoding by Maximization of Mutual Information Transfer

<p/> <p>The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper, a novel theoretical framework for improving the performance of turbo decoding schemes that use the max-log-MAP algorithm is proposed. This fr...

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Bibliographic Details
Main Authors: Karimi Hamid Reza, Claussen Holger, Mulgrew Bernard
Format: Article
Language:English
Published: SpringerOpen 2005-01-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/ASP.2005.820
Description
Summary:<p/> <p>The demand for low-cost and low-power decoder chips has resulted in renewed interest in low-complexity decoding algorithms. In this paper, a novel theoretical framework for improving the performance of turbo decoding schemes that use the max-log-MAP algorithm is proposed. This framework is based on the concept of maximizing the transfer of mutual information between the component decoders. The improvements in performance can be achieved by using optimized iteration-dependent correction weights to scale the a priori information at the input of each component decoder. A method for the offline computation of the correction weights is derived. It is shown that a performance which approaches that of a turbo decoder using the optimum MAP algorithm can be achieved, while maintaining the advantages of low complexity and insensitivity to input scaling inherent in the max-log-MAP algorithm. The resulting improvements in convergence of the turbo decoding process and the expedited transfer of mutual information between the component decoders are illustrated via extrinsic information transfer (EXIT) charts.</p>
ISSN:1687-6172
1687-6180