Turbo decoding of product codes using adaptive belief propagation

Authors:
Christophe Jégo;Warren J. Gross
Affiliations:
Institut Telecom, Telecom Bretagne, CNRS, Lab-STICC, UMR, Electronic Engineering Department, Brest Cedex 3 and Université Européenne de Bretagne, France;Department of Electrical and Computer Engineering, McGill University, Montreal, Canada
Venue:
IEEE Transactions on Communications
Year:
2009

Citing 2
Cited 0

Iterative Soft-Input Soft-Output Decoding of Reed–Solomon Codes by Adapting the Parity-Check Matrix

IEEE Transactions on Information Theory
Iterative algebraic soft-decision list decoding of Reed-Solomon codes

IEEE Journal on Selected Areas in Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Adaptive Belief Propagation (ABP) algorithm was recently proposed by Jiang and Narayanan for the soft decoding of Reed-Solomon (RS) codes. In this paper, simplified versions of this algorithm are investigated for the turbo decoding of product codes. The complexity of the Turbo-oriented Adaptive Belief propagation (TAB) algorithm is significantly reduced by moving the matrix adaptation step outside of the belief propagation iteration loop. A reduced-complexity version of the TAB algorithm that offers a trade-off between performance and complexity is also proposed. Simulation results for the turbo decoding of product codes show that belief propagation based on adaptive parity check matrices is a practical alternative to the currently very popular Chase-Pyndiah algorithm.