Proceedings Article10.1109/ICCC49849.2020.9238855
A Parallel and Memory-Efficient Decoding for Spatially-Coupled LDPC Codes
Qihao Wu,Lihong Lv,Yanjun Yao,Sheng Wu +3 more
- 09 Aug 2020
- pp 1016-1021
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TL;DR: Simulation results show that the new decoding greatly reduces decoding latency and requires less memory, and there is no performance degradation.
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Abstract: In this paper, we propose a parallel and memory-efficient decoding for spatially-coupled low-density parity-check (SC LDPC) codes. The new decoding was obtained by applying parallel architecture and efficient memory management to the windowed decoding. Simulation results show that the new decoding greatly reduces decoding latency and requires less memory, and there is no performance degradation. The advantage of the proposed decoding make it appealing in practical applications, especially in low latency scenario.
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Citations
Low-Complexity Sliding Window Decoding of Spatially-Coupled LDPC Codes Constructed from Short 5G NR LDPC
Abdoul-Hadi Konfé,Pasteur Poda,Raphaël Le Bidan +2 more
- 23 Jul 2024
TL;DR: This study optimizes sliding window decoding of spatially-coupled LDPC codes by proposing a new design based on 5G short LDPC codes, reducing decoding complexity by 30% without significant performance degradation.
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Threshold Saturation via Spatial Coupling: Why Convolutional LDPC Ensembles Perform So Well over the BEC
TL;DR: The fundamental mechanism that explains why “convolutional-like” or “spatially coupled” codes perform so well is described, and it is conjecture that for a large range of graphical systems a similar saturation of the “dynamical” threshold occurs once individual components are coupled sufficiently strongly.
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A reduced complexity decoder architecture via layered decoding of LDPC codes
D.E. Hocevar
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TL;DR: The previously devised irregular partitioned permutation LDPC codes have a construction that easily accommodates a layered decoding and it is shown that the decoding performance is improved by a factor of two in the number of iterations required.
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Windowed Decoding of Protograph-Based LDPC Convolutional Codes Over Erasure Channels
Aravind R. Iyengar,Marco Papaleo,Paul H. Siegel,Jack K. Wolf,Alessandro Vanelli-Coralli,Giovanni Emanuele Corazza +5 more
TL;DR: The structure of LDPC convolutional code ensembles is suitable to obtain performance close to the theoretical limits over the memoryless erasure channel, both for the BP decoder and windowed decoding but the same structure imposes limitations on the performance over erasure channels with memory.
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Windowed Decoding of Protograph-based LDPC Convolutional Codes over Erasure Channels
Aravind R. Iyengar,Marco Papaleo,Paul H. Siegel,Jack K. Wolf,Alessandro Vanelli-Coralli,Giovanni Emanuele Corazza +5 more
TL;DR: In this article, a windowed decoding scheme for LDPC convolutional codes that is based on the belief propagation (BP) algorithm is considered and the performance of these ensembles and codes over erasure channels with and without memory.
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