Iterative Soft-Input Soft-Output Decoding of Reed–Solomon Codes by Adapting the Parity-Check Matrix
Jing Jiang
Narayanan, K.R.
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX;
This paper appears in: Information Theory, IEEE Transactions on
Publication Date: Aug. 2006
Volume: 52,
Issue: 8
On page(s): 3746-3756
ISSN: 0018-9448
INSPEC Accession Number: 9010881
Digital Object Identifier: 10.1109/TIT.2006.878176
Current Version Published: 2006-07-24
Abstract
An iterative algorithm is presented for soft-input soft-output (SISO) decoding of Reed-Solomon (RS) codes. The proposed iterative algorithm uses the sum-product algorithm (SPA) in conjunction with a binary parity-check matrix of the RS code. The novelty is in reducing a submatrix of the binary parity-check matrix that corresponds to less reliable bits to a sparse nature before the SPA is applied at each iteration. The proposed algorithm can be geometrically interpreted as a two-stage gradient descent with an adaptive potential function. This adaptive procedure is crucial to the convergence behavior of the gradient descent algorithm and, therefore, significantly improves the performance. Simulation results show that the proposed decoding algorithm and its variations provide significant gain over hard-decision decoding (HDD) and compare favorably with other popular soft-decision decoding methods
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