.png){kind=icon}
返回
A Hypergraph Filtering Based Iterative Decoding Approach for Linear Channel Codes
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2021.3079283.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Efficient decoding for general linear channel codes has been a long standing problem. Message passing type algorithms can achieve near-optimal performance for channel codes with sparse check matrices and long code-lengths, but they may suffer from obvious performance loss when the aforementioned two conditions are not satisfied. In this paper, we propose an alternative hypergraph filtering based decoding scheme based on recently developed hypergraph signal processing (HGSP) frameworks. Specifically, we model the coded sequence as a hypergraph signal by regarding each coded bit as a vertex and representing each check constraint by a hyperedge. We then map the message passing in iterative decoding algorithms to the signal shifting in HGSP, based on which a hypergraph filtering (HF) based decoding scheme is developed. By further combining the modified random redundant iterative decoding (mRRD) technique, we finally develop a novel HF-mRRD scheme to approach the near-optimal decoding performance. Simulation results on both Hamming codes and BCH codes show that the proposed scheme obtains significant performance gains over standard message passing type algorithms, and achieve comparable or even better performance than the state-of-the-art deep learning based schemes.
Keyword:
Iterative decoding
Signal processing algorithms
Message passing
Complexity theory
Maximum likelihood decoding
Sparse matrices
Standards
Channel codes
message passing
hypergraph signal processing
hypergraph filtering based decoding
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Reduced complexity iterative decoding of low-density parity check codes based on belief propagation基于置信传播的低密度奇偶校验码迭代译码复杂度降低
PREAI
分享收藏Oral Idarubicin as a Single Agent Therapy in Patients with Relapsed or Resistant Multiple Myeloma
PREAI
分享收藏Disease Prediction by Machine Learning Over Big Data From Healthcare Communities.png)
IEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容