A two-dimensional product code with robust soft-decision decoding

Freeman, D.F.; Michelson, A.M.

doi:10.1109/26.539758

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…Without knowing the impulsive noise probability density function, one promising solution is to identify the symbols that are likely to be corrupted by large amplitude noise and ignore (erase) them in decoding. Two examples are the region-based erasure marking schemes [3] [4] and the Viterbi's ratio-threshold technique [15] [16]. By doing so, the metric mismatch problem can be alleviated.…”

Section: Introductionmentioning

confidence: 98%

Joint Erasure Marking and List Viterbi Algorithm for Decoding in Unknown Non-Gaussian Noise

Mow

Siu

2008

IEEE Trans. Wireless Commun.

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In many real-world communication systems, the channel noise is non-Gaussian due to the presence of impulsive noise as well as the background Gaussian noise. In such situations, the conventional Euclidean distance based decoder may suffer from the problem of severe metric mismatch. To overcome the problem, we recently proposed the joint erasure marking and Viterbi algorithm (JEVA) as a robust trellis decoder that does not require an estimate of the impulsive noise distribution. In this work, two ways to further improve JEVA are presented for systems with an error detecting code. Specifically, the JEVA is integrated with the list Viterbi algorithm (LVA) to form the two-dimensional joint erasure marking and list Viterbi algorithm (JELVA) and the switched JELVA, respectively. By combining the respective strengths of the JEVA and the LVA, the integrated decoding schemes are able to achieve significant performance gains over the original JEVA and achieve a wide range of performance-complexity-delay tradeoffs.Index Terms-Non-Gaussian noise, list Viterbi algorithm, erasure decoding, joint erasure marking and decoding.

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Section: Introductionmentioning

confidence: 98%

Joint Erasure Marking and List Viterbi Algorithm for Decoding in Unknown Non-Gaussian Noise

Mow

Siu

2008

IEEE Trans. Wireless Commun.

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“…The convergence rate and stability of product codes iterative decoding were studied based on a geometric framework [55]. March 7, 2016 DRAFT Product codes with mixed convolutional and block components were also found efficient in presence of impulsive noise [22]. In addition, iterated Reed-Muller product codes were shown to exhibit good decoding thresholds for the binary erasure channel, but at high and low coding rates only [65].…”

Section: Introductionmentioning

confidence: 99%

Edge Coloring and Stopping Sets Analysis in Product Codes With MDS Components

Jardel

Boutros

2017

IEEE Trans. Inform. Theory

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We consider non-binary product codes with MDS components and their iterative row-column algebraic decoding on the erasure channel. Both independent and block erasures are considered in this paper. A compact graph representation is introduced on which we define double-diversity edge colorings where M ℵ itself is small with respect to the huge cardinality of the coloring ensemble. The performance of MDS-based product codes with and without double-diversity coloring is analyzed in presence of both block and independent erasures. In the latter case, ML and iterative decoding are proven to coincide at small channel erasure probability. Furthermore, numerical results show excellent performance in presence of unequal erasure probability due to double-diversity colorings.

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Bit-Interleaved Coded Modulation in the Presence of Unknown Impulsive Noise

Mow

Siu

2006

2006 IEEE International Conference on Communications

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A two-dimensional product code with robust soft-decision decoding

Cited by 5 publications

References 3 publications

Joint Erasure Marking and List Viterbi Algorithm for Decoding in Unknown Non-Gaussian Noise

Joint Erasure Marking and List Viterbi Algorithm for Decoding in Unknown Non-Gaussian Noise

Edge Coloring and Stopping Sets Analysis in Product Codes With MDS Components

Bit-Interleaved Coded Modulation in the Presence of Unknown Impulsive Noise

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