Soft‐input bit‐flipping decoding of generalised concatenated codes for application in non‐volatile flash memories

Rajab, Mohammed; Shavgulidze, Sergo; Freudenberger, Jürgen

doi:10.1049/iet-com.2018.5534

Cited by 9 publications

(18 citation statements)

References 38 publications

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“…and GCCs show large potential applications, e.g., in data transmission systems [36] and Flash memory [37], [38]. TPCs and GTPCs exhibit large advantages in magnetic storage systems [39]- [42], Flash memory [43], [44] and in constructing locally repairable codes for distributed storage systems [45]- [47].…”

Section: Classical Concatenated Codesmentioning

confidence: 99%

Asymmetric Quantum Concatenated and Tensor Product Codes With Large Z-Distances

Fan

Wang

et al. 2021

IEEE Trans. Commun.

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In many quantum channels, dephasing errors occur more frequently than the amplitude errorsa phenomenon that has been exploited for performance gains and other benefits through asymmetric quantum codes (AQCs). In this paper, we present a new construction of AQCs by combining classical concatenated codes (CCs) with tensor product codes (TPCs), called asymmetric quantum concatenated and tensor product codes (AQCTPCs) which have the following three advantages. First, only the outer codes in AQCTPCs need to satisfy the orthogonal constraint in quantum codes, and any classical linear code can be used for the inner, which makes AQCTPCs very easy to construct. Second, most AQCTPCs are highly degenerate, which means they can correct many more errors than their classical TPC counterparts. Consequently, we construct several families of AQCs with better parameters than known results in the literature. Especially, we derive a first family of binary AQCs with the Zdistance larger than half the block length. Third, AQCTPCs can be efficiently decoded although they

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Section: Classical Concatenated Codesmentioning

confidence: 99%

Asymmetric Quantum Concatenated and Tensor Product Codes With Large Z-Distances

Fan

Wang

et al. 2021

IEEE Trans. Commun.

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“…Consequently, they have long been in the focus of coding theorists as well as coding practitioners [3]. There is vigorous research concerning these codes and their decoding algorithms even 60 years after their discovery, which could be documented by the following selected references [6][7][8][9][10][11][12]. Therefore, there are numerous known algorithms for their encoding as well as for decoding.…”

Section: Some Notes On Rs Code Decodingmentioning

confidence: 99%

Erasure decoding of five times extended Reed-Solomon codes

Rakús

Farkas

Palenik

2019

Journal of Electrical Engineering

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“…For instance, product code constructions based on BCH codes were proposed in [1–3]. Moreover, generalized concatenated codes (GCC) with inner BCH codes were investigated in [4–8]. Hardware architectures for such codes were proposed for instance in [9–13].…”

Section: Introductionmentioning

confidence: 99%

“…For instance, product code constructions based on BCH codes were proposed in [1][2][3]. Moreover, generalized concatenated codes (GCC) with inner BCH codes were investigated in [4][5][6][7][8].…”

Section: Introductionmentioning

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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Soft‐input bit‐flipping decoding of generalised concatenated codes for application in non‐volatile flash memories

Cited by 9 publications

References 38 publications

Asymmetric Quantum Concatenated and Tensor Product Codes With Large Z-Distances

Asymmetric Quantum Concatenated and Tensor Product Codes With Large Z-Distances

Erasure decoding of five times extended Reed-Solomon codes

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

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