Euclidean Geometry-Based Spatially Coupled LDPC Codes for Storage

Xie, Yuan; Yang, Lei; Kang, Peng; Yuan, Jinhong

doi:10.1109/jsac.2016.2603703

Cited by 31 publications

(13 citation statements)

References 34 publications

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“…Based on A and P A|X , we can compute the optimal SDQ Λ c by DP [36] to generate Γ c as defined by (3), and Q c can be obtained from (5). Meanwhile, for a realization s of the C2V message S ∈ S, we can compute the probability of S conditioned on the channel input bit X, i.e., P S|X , as…”

Section: A Mim-qbp Decoder Design At Cn For Irregular Ldpc Codesmentioning

confidence: 99%

Generalized Mutual Information-Maximizing Quantized Decoding of LDPC Codes with Layered Scheduling

Peng¹,

Cai²,

He³

et al. 2020

Preprint

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In this paper, we propose a general framework of the mutual infomration-maximizing (MIM) quantized decoding for low-density parity-check (LDPC) codes, which can outperform the state-of-the-art lookup table (LUT) decoder by using simple mappings and fixed-point additions for the node updates. Our decoding method is generic in the sense that it can be applied to LDPC codes with arbitrary degree distributions, and it can be implemented based on either the belief propagation (BP) algorithm or the min-sum (MS) algorithm, leading to the MIM quantized BP (MIM-QBP) decoder and the MIM quantized MS (MIM-QMS) decoder, respectively. In particular, we approximate the check node (CN) update of the MIM-QBP decoder by a max-product operation and obtain the MIM-QMS decoder, which simplifies the decoder design and requires less resource consumption. To avoid the precision degradation, we introduce a dynamic reconstruction method to optimize the variable node update for different iterations. Some practical aspects of the proposed decoders such as the design and decoding complexity are also discussed. Simulation results show that the MIM-QBP decoder outperforms the LUT decoders in the waterfall region with both 3-bit and 4-bit precision. Moreover, the 4-bit MIM-QMS decoder can even surpass the floating-point BP decoder in the error-floor region.

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Section: A Mim-qbp Decoder Design At Cn For Irregular Ldpc Codesmentioning

confidence: 99%

Generalized Mutual Information-Maximizing Quantized Decoding of LDPC Codes with Layered Scheduling

Peng¹,

Cai²,

He³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…It was firstly introduced in [1] for constructing convolutional low-density parity-check (LDPC) codes, which is also known as spatially coupled LDPC (SC-LDPC) codes. Extensive research has been conducted on SC-LDPC codes (see [2]- [4] and the references therein) since then. In addition, the spatial coupling technique has also been applied to turbo-like codes (SC-TCs), including parallel and serially concatenated convolutional codes [5], hybrid concatenated convolutional codes [6], laminated turbo codes [7], and braided convolutional codes [8].…”

Section: Introductionmentioning

confidence: 99%

Partially Information Coupled Duo-Binary Turbo Codes

Qiu

Yuan

2020

2020 IEEE International Symposium on Information Theory (ISIT)

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Partially information coupled turbo codes (PIC-TCs) is a class of spatially coupled turbo codes that can approach the BEC capacity while keeping the encoding and decoding architectures of the underlying component codes unchanged. However, PIC-TCs have significant rate loss compared to its component rate-1 3 turbo code, and the rate loss increases with the coupling ratio. To absorb the rate loss, in this paper, we propose the partially information coupled duo-binary turbo codes (PIC-dTCs). Given a rate-1 3 turbo code as the benchmark, we construct a duo-binary turbo code by introducing one extra input to the benchmark code. Then, parts of the information sequence from the original input are coupled to the extra input of the succeeding code blocks. By looking into the graph model of PIC-dTC ensembles, we derive the exact density evolution equations of the PIC-dTC ensembles, and compute their belief propagation decoding thresholds on the binary erasure channel. Simulation results verify the correctness of our theoretical analysis, and also show significant error performance improvement over the uncoupled rate-1 3 turbo codes and existing designs of spatially coupled turbo codes.

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“…Several classes of spatially coupled codes have been proposed in the literature. Some well-known examples such as spatially coupled LDPC (SC-LDPC) codes [2]- [4], spatially coupled turbo-like codes (SC-TCs) [5] whose component codes includes parallel concatenated convolutional codes (PC-CCs) [6] and serial concatenated convolutional codes (SCCCs) [7], braided convolutional codes (BCCs) [8] and staircase codes [9], [10], have all reported the close-to-capacity performance. Most importantly, it has been proved in [4] and [5] that the belief-propagation (BP) decoding thresholds of the SC-LDPC and SC-TC ensembles can converge to the maximum-a-posteriori (MAP) decoding thresholds of their respective underlying uncoupled ensembles.…”

Section: Introductionmentioning

confidence: 99%

“…Spatially coupled codes, originally introduced in [1] as convolutional low-density parity-check (LDPC) codes, have now been recognized as promising candidates for a range of applications such as optical communication and data storage systems [2]. These codes are constructed from a sequence of component codes coupled in a certain structure.…”

Section: Introductionmentioning

confidence: 99%

Density Evolution Analysis of Partially Information Coupled Turbo Codes on the Erasure Channel

Qiu

Xie

et al. 2019

2019 IEEE Information Theory Workshop (ITW)

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In this paper, we investigate the performance of a class of spatially coupled codes, namely partially information coupled turbo codes (PIC-TCs) over the binary erasure channel (BEC). This class of codes enjoy flexible code rate adjustment by varying the coupling ratio. Moreover, the coupling method can be directly applied to any component codes without changing the encoding and decoding architectures of the underlying component codes. However, the theoretical performance of PIC-TCs has not been fully investigated. For this work, we consider the codes that have coupling memory m and study the corresponding graph model. We then derive the exact density evolution equations for these code ensembles with any given coupling ratio and coupling memory m to precisely compute their belief propagation decoding thresholds for the BEC. Our simulation results verify the correctness of our theoretical analysis and also show better error performance over uncoupled turbo codes with a variety of code rates on the BEC.

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Euclidean Geometry-Based Spatially Coupled LDPC Codes for Storage

Cited by 31 publications

References 34 publications

Generalized Mutual Information-Maximizing Quantized Decoding of LDPC Codes with Layered Scheduling

Generalized Mutual Information-Maximizing Quantized Decoding of LDPC Codes with Layered Scheduling

Partially Information Coupled Duo-Binary Turbo Codes

Density Evolution Analysis of Partially Information Coupled Turbo Codes on the Erasure Channel

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