This paper proposes the low-complexity Chase (LCC) decoding for Hermitian codes, which is facilitated by the re-encoding transform (reT) and fast factorization (FF). By identifying η unreliable received symbols, 2η ...
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The interpolation based algebraic decoding for reed-Solomon (RS) codes can correct errors beyond half of the code's minimum Hamming distance through constructing a minimum polynomial Q(x,y) and finding its y-roots...
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ISBN:
(纸本)9781538692912
The interpolation based algebraic decoding for reed-Solomon (RS) codes can correct errors beyond half of the code's minimum Hamming distance through constructing a minimum polynomial Q(x,y) and finding its y-roots. The progressive algebraic soft decoding (PASD) constructs Q(x, y) with a progressively enlarged y-degree and terminates once the message is decoded, adapting the decoding capability and computation to the channel. This paper proposes the re-encoding transformed PASD algorithm, in which Q(x, y) is progressively constructed by the low-complexity module minimization (MM) technique. re-encoding transform (reT) results in a common divisor for polynomials of the image of the submodule basis. It can be removed, leading to a simpler image expansion and reduction. Consequently, Q(x, y) is constructed through the isomorphic image of the progressively enlarged submodule basis. Our complexity analysis characterizes the complexity reduction brought by the transform and shows high rate codes benefit a greater complexity reduction.
The algebraic soft decoding (ASD) algorithm for reed-Solomon (RS) codes can correct errors beyond the half distance bound with a polynomial time complexity. However, the decoding complexity remains high due to the com...
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The algebraic soft decoding (ASD) algorithm for reed-Solomon (RS) codes can correct errors beyond the half distance bound with a polynomial time complexity. However, the decoding complexity remains high due to the computationally expensive interpolation that is an iterative polynomial construction process. By performing the interpolation progressively, the progressive ASD (PASD) algorithm can adapt the decoding computation to the need, leveraging the average complexity of multiple decoding events. But the complexity reduction is realised at the expense of system memory, since the intermediate interpolation information needs to be memorised. Addressing this challenge, this paper proposes an improved PASD (I-PASD) algorithm that can alleviate the memory requirement and further reduce the decoding complexity. A condition on expanding the set of interpolated polynomials will be introduced, which excepts the need of performing iterative updates for the newly introduced polynomial. Further incorporating the re-encoding transform, the I-PASD algorithm can reduce the decoding complexity over the PASD algorithm by a factor of 1/3 and its memory requirement is at most half of the PASD algorithm. The complexity and memory requirement will be theoretically analysed and validated by numerical results. Finally, we will confirm that the complexity and memory reductions arerealised with preserving the error-correction capability of the ASD algorithm. (C) 2016 Elsevier B.V. All rights reserved.
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