Turbo decoding of product codes using adaptive belief propagation

Christophe Jego (1) , Warren J. Gross (2)

1 IMS - Laboratoire de l'intégration, du matériau au système
2 McGill University = Université McGill [Montréal, Canada]

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.

Mots clés: Chase-Pyndiah algorithm; RS codes; Reed-Solomon codes; adaptive parity check matrices; complexity reduction; matrix adaptation step; performance-complexity tradeoff; product codes; soft decoding; turbo decoding; turbo-oriented adaptive belief propagation algorithms; computational complexity; decoding; matrix algebra; turbo codes

Domaines: Electronique

Christophe Jego, Warren J. Gross. Turbo decoding of product codes using adaptive belief propagation. IEEE Transactions on Communications, 2009, 57 (10), pp.2864 -2867. ⟨10.1109/TCOMM.2009.10.070277⟩. ⟨hal-00573252⟩