空间耦合低密度奇偶校验码残差滑窗译码算法

周华; 李子杰

doi:10.11999/JEIT230288

空间耦合低密度奇偶校验码残差滑窗译码算法

doi: 10.11999/JEIT230288

周华^,,
李子杰

南京信息工程大学电子与信息工程学院南京 210044

基金项目: 国家自然科学基金(61771248, 62001238)

详细信息

作者简介:
周华：男，博士，副教授，研究方向为信息论编码、无线通信等

李子杰：男，硕士生，研究方向为现代信道编码技术

通讯作者:
周华　hzhou@nuist.edu.cn

中图分类号: TN911.22
计量
- 文章访问数: 532
- HTML全文浏览量: 202
- PDF下载量: 48
- 被引次数: 0
出版历程
- 收稿日期: 2023-04-18
- 修回日期: 2023-08-09
- 网络出版日期: 2023-08-19
- 刊出日期: 2024-03-27

Residual Sliding Window Decoding Algorithm for Spatially-coupled Low-density Parity-check Codes

ZHOU Hua^,,
LI Zijie

School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

Funds: The National Natural Science Foundation of China (61771248, 62001238)

摘要

摘要: 针对空间耦合低密度奇偶校验(SC-LDPC)码滑窗译码(SWD)算法中错误传播导致的高误码率问题，该文提出基于动态残差的滑窗译码(RSWD)算法。通过在窗口内计算边信息更新前后的残差值，动态选择可靠度最低(残差值最大)的边信息优先更新，降低边信息无效更新的频率，提高窗内译码收敛速度。仿真结果表明：相比于传统SWD算法，RSWD算法在窗口中各位置的误比特数明显降低，抑制错误传播效果明显；在高信噪比(SNR)区域或者低迭代次数的情况下，RSWD算法的误码率性能优于SWD算法；此外，将动态残差应用到消息复用(MR)和窗口扩展(WE)两种窗译码算法中，亦能得到类似结论，提升窗译码性能。
- 空间耦合低密度奇偶校验码 /
- 错误传播 /
- 滑窗译码 /
- 残差算法
Abstract: A dynamic Residual Sliding Window Decoding (RSWD) algorithm is proposed in this paper to reduce the high bit error rate caused by error propagation in the Sliding Window Decoding (SWD) algorithm for Spatially-Coupled Low-Density Parity-Check (SC-LDPC) codes. By calculating the residuals of edge information before and after updates, RSWD algorithm dynamically updates the edge of the lowest reliability (or equivalently maximum residual value) with priority, resulting in reduction in the frequency of ineffective edge updating and improvement in the convergence speed of sliding window decoding. The simulation results show that compared to the traditional SWD algorithm, the proposed RSWD algorithm successfully decreases the number of error bit at various positions in the window and shows significant effect on suppressing error propagation; in the high Signal-to-Noise Ratio (SNR) region or in the case of small number of decoding iterations, RSWD presents superior bit error rate performance to SWD; Applying dynamic residuals to both Message Reuse(MR) and Window Extension(WE) window decoding algorithms can also obtain similar observations and improve the decoding performance.
- Spatially Coupled Low-Density Parity-Check (SC-LDPC) codes /
- Error propagation /
- Sliding window decoding /
- Residual algorithm

HTML全文

图 1 SC-LDPC码原模图的构造过程

下载: 全尺寸图片幻灯片

图 2 SC-LDPC码滑窗译码

下载: 全尺寸图片幻灯片

图 3 滑窗译码中的错误传播

下载: 全尺寸图片幻灯片

图 4 SWD算法和RSWD算法窗口各位置的误码率比较

下载: 全尺寸图片幻灯片

图 5 仿真使用的SC-LDPC码校验矩阵

下载: 全尺寸图片幻灯片

图 6 SWD算法、MR-SWD算法、RSWD算法和MR-RSWD算法译码性能比较

下载: 全尺寸图片幻灯片

图 7 最大迭代次数对SWD算法、MR-SWD算法、RSWD算法和MR-RSWD算法误码率性能的影响

下载: 全尺寸图片幻灯片

图 8 SWD算法、WE-SWD算法、RSWD算法和WE-RSWD算法译码性能比较

下载: 全尺寸图片幻灯片

图 9 最大迭代次数对SWD算法、WE-SWD算法、RSWD算法和WE-RSWD算法误码率性能的影响

下载: 全尺寸图片幻灯片

图 10 滑窗译码算法复杂度

下载: 全尺寸图片幻灯片

参考文献(18)

[1]	JIMENEZ A and ZIGANGIROV K S. Time-varying periodic convolutional codes with low-density parity-check matrix[J]. IEEE Transactions on Information Theory, 1999, 45(6): 2181–2191. doi: 10.1109/18.782171.
[2]	SHI Xiangyi, ZHAO Danfeng, TIAN Hai, et al. Design of time-invariant SC-LDPC codes based on PEG algorithm[C]. 2020 IEEE Computing, Communications and IoT Applications, Beijing, China, 2020: 1–5.
[3]	KUDEKAR S, RICHARDSON T J, and URBANKE R L. Threshold saturation via spatial coupling: Why convolutional LDPC ensembles perform so well over the BEC[J]. IEEE Transactions on Information Theory, 2011, 57(2): 803–834. doi: 10.1109/TIT.2010.2095072.
[4]	XIE Cong, YANG Jian, TIAN Hai, et al. A random construction method of SC-LDPC code with changed check structure[C]. 2021 IEEE 21st International Conference on Communication Technology, Tianjin, China, 2021: 105–110.
[5]	KHITTIWITCHAYAKUL S, PHAKPHISUT W, and SUPNITHI P. Reduced complexity window decoding of spatially coupled LDPC codes for magnetic recording systems[J]. IEEE Transactions on Magnetics, 2018, 54(11): 9401205. doi: 10.1109/TMAG.2018.2832252.
[6]	KOGANEI I Y, YOFUNE M, LI Cong, et al. SC-LDPC code with nonuniform degree distribution optimized by using genetic algorithm[J]. IEEE Communications Letters, 2016, 20(5): 874–877. doi: 10.1109/LCOMM.2016.2545652.
[7]	KWAK H Y, NO S J, and PARK H. Design of irregular SC-LDPC codes with non-uniform degree distributions by linear programming[J]. IEEE Transactions on Communications, 2019, 67(4): 2632–2646. doi: 10.1109/TCOMM.2018.2889850.
[8]	DEHAGHANI A E, SADEGHI M R, and AMIRZADE F. Improving asymptotic properties of loop construction of SC-LDPC chains over the BEC[J]. IEEE Communications Letters, 2022, 26(3): 495–499. doi: 10.1109/LCOMM.2021.3138613.
[9]	IYENGAR A R, PAPALEO M, SIEGEL P H, et al. Windowed decoding of protograph-based LDPC convolutional codes over erasure channels[J]. IEEE Transactions on Information Theory, 2012, 58(4): 2303–2320. doi: 10.1109/TIT.2011.2177439.
[10]	ALI I, KIM J H, KIM S H, et al. Improving windowed decoding of SC LDPC codes by effective decoding termination, message reuse, and amplification[J]. IEEE Access, 2018, 6: 9336–9346. doi: 10.1109/ACCESS.2017.2771375.
[11]	ZHU Min, MITCHELL D G M, LENTMAIER M, et al. Combating error propagation in window decoding of braided convolutional codes[C]. 2018 IEEE International Symposium on Information Theory, Vail, USA, 2018: 1380–1384.
[12]	吴皓威, 武小飞, 邹润秋, 等. 空间耦合LDPC码的分层译码算法[J]. 电子与信息学报, 2020, 42(8): 1881–1887. doi: 10.11999/JEIT190626. WU Haowei, WU Xiaofei, ZOU Runqiu, et al. A layered decoding algorithm for spatially-coupled LDPC codes[J]. Journal of Electronics &Information Technology, 2020, 42(8): 1881–1887. doi: 10.11999/JEIT190626.
[13]	张娅妹, 周林, 陈辰, 等. 窗口可变的空间耦合LDPC码滑窗译码算法[J]. 西安电子科技大学学报, 2020, 47(3): 128–134. doi: 10.19665/j.issn1001-2400.2020.03.018. ZHANG Yamei, ZHOU Lin, CHEN Chen, et al. Sliding window decoding algorithm for spatially coupled LDPC codes with a variable window[J]. Journal of Xidian University, 2020, 47(3): 128–134. doi: 10.19665/j.issn1001-2400.2020.03.018.
[14]	MCMILLON E and KELLEY C A. Cycle-free windows of SC-LDPC codes[C]. 2022 IEEE International Symposium on Information Theory, Espoo, Finland, 2022: 390–395.
[15]	TARABLE A, FERRARI M, and BARLETTA L. Two is better than one: Reducing the loss of the window decoder for SC-LDPC codes[C]. 2020 IEEE Information Theory Workshop, Riva del Garda, Italy, 2021: 1–5.
[16]	HERRMANN M, WEHN N, THALMAIER M, et al. A 336 Gbit/s full-parallel window decoder for spatially coupled LDPC codes[C]. 2021 Joint European Conference on Networks and Communications & 6G Summit, Porto, Portugal, 2021: 508–513.
[17]	CASADO A I V, GRIOT M, and WESEL R D. Informed dynamic scheduling for belief-propagation decoding of LDPC codes[C]. 2007 IEEE International Conference on Communications, Glasgow, UK, 2007: 932–937.
[18]	KLAIBER K, CAMMERER S, SCHMALEN L, et al. Avoiding burst-like error patterns in windowed decoding of spatially coupled LDPC codes[C]. 2018 IEEE 10th International Symposium on Turbo Codes & Iterative Information Processing, Hong Kong, China, 2018: 1–5.