Soft input decoder for high‐rate generalised concatenated codes

Spinner, Jens; Rohweder, Daniel; Freudenberger, Jürgen

doi:10.1049/iet-cds.2017.0347

Cited by 8 publications

(27 citation statements)

References 25 publications

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“…This reduces the overall decoding complexity significantly because the BMA typically dominates the computational complexity. Consider for instance the RS decoder architectures for error and erasure decoding reported in [30,31]. In [30], the BMA requires 84% of the total logic of the decoder for an RS code of length n = 508, whereas the syndrome calculation and the Forney algorithm need only 11%.…”

Section: Erasure Only Decoding Of Rs Codesmentioning

confidence: 99%

“…In [30], the BMA requires 84% of the total logic of the decoder for an RS code of length n = 508, whereas the syndrome calculation and the Forney algorithm need only 11%. Similarly, in [31] a decoder for RS codes of length n = 334 is considered. The BMA occupies 51%, the syndrome calculation 14%, and the Forney algorithm 14% of the area for logic, respectively.…”

Section: Erasure Only Decoding Of Rs Codesmentioning

confidence: 99%

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A New Class of Q-Ary Codes for the McEliece Cryptosystem

Freudenberger

Thiers

2021

Cryptography

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The McEliece cryptosystem is a promising candidate for post-quantum public-key encryption. In this work, we propose q-ary codes over Gaussian integers for the McEliece system and a new channel model. With this one Mannheim error channel, errors are limited to weight one. We investigate the channel capacity of this channel and discuss its relation to the McEliece system. The proposed codes are based on a simple product code construction and have a low complexity decoding algorithm. For the one Mannheim error channel, these codes achieve a higher error correction capability than maximum distance separable codes with bounded minimum distance decoding. This improves the work factor regarding decoding attacks based on information-set decoding.

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Section: Erasure Only Decoding Of Rs Codesmentioning

confidence: 99%

Section: Erasure Only Decoding Of Rs Codesmentioning

confidence: 99%

A New Class of Q-Ary Codes for the McEliece Cryptosystem

Freudenberger

Thiers

2021

Cryptography

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“…The positions altered by the bit-flipping patterns can be determined by sorting the soft-values, but the positions altered by the algebraic decoder are only known after each algebraic decoding step. Hence, all LLR values are stored in [13]. In order to reduce the RAM requirements, we store only the positions and the LLR values corresponding to the least reliable values, where we increase the search depth for the LLR values.…”

Section: Gc Decodingmentioning

confidence: 99%

Reduced complexity hard‐ and soft‐input BCH decoding with applications in concatenated codes

Freudenberger

Bailon

Safieh

2021

IET Circuits, Devices & Syst

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Error correction coding for optical communication and storage requires high rate codes that enable high data throughput and low residual errors. Recently, different concatenated coding schemes were proposed that are based on binary BCH codes with low error correcting capabilities. In this work, low-complexity hard-and soft-input decoding methods for such codes are investigated. We propose three concepts to reduce the complexity of the decoder. For the algebraic decoding we demonstrate that Peterson's algorithm can be more efficient than the Berlekamp-Massey algorithm for single, double, and triple error correcting BCH codes. We propose an inversion-less version of Peterson's algorithm and a corresponding decoding architecture. Furthermore, we propose a decoding approach that combines algebraic hard-input decoding with soft-input bitflipping decoding. An acceptance criterion is utilised to determine the reliability of the estimated codewords. For many received codewords the stopping criterion indicates that the hard-decoding result is sufficiently reliable, and the costly soft-input decoding can be omitted. To reduce the memory size for the soft-values, we propose a bit-flipping decoder that stores only the positions and soft values of a small number of code symbols. This method significantly reduces the memory requirements and has little adverse effect on the decoding performance. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Mostly, GC codes use components codes where the outer RS codes have a larger alphabet size than the inner BCH codes. With such constructions the decoder complexity is dominated by the logic for the RS decoder [18, 27]. Using stronger inner codes reduces the decoder complexity for the outer codes.…”

Section: Gc Codesmentioning

confidence: 99%

“…This construction enables high‐rate GC codes. Moreover, these GC codes have a low complexity compared to long BCH codes and are well suited for fast hardware decoding architectures [18, 27]. However, with soft‐input decoding the inner SPC limits the coding gain [28].…”

Section: Introductionmentioning

confidence: 99%