Expander graph arguments for message-passing algorithms

被引:64
|
作者
Burshtein, D [1 ]
Miller, G [1 ]
机构
[1] Tel Aviv Univ, Dept Elect Engn Syst, IL-69978 Tel Aviv, Israel
关键词
belief propagation; expander graph; iterative decoding; low-density parity-check (LDPC) codes;
D O I
10.1109/18.910588
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We show how expander-based arguments may be used to prove that message-passing algorithms can correct a linear number of erroneous messages. The implication of this result is that when the block length is sufficiently large, once a message-passing algorithm has corrected a sufficiently large fraction of the errors, it will eventually correct all errors. This result is then combined with known results on the ability of message-passing algorithms to reduce the number of errors to an arbitrarily small fraction for relatively high transmission rates. The results hold for various message-passing algorithms, including Gallager's hard-decision and soft-decision (with clipping) decoding algorithms, Our results assume low-density parity-check (LDPC) codes based on an irregular bipartite graph.
引用
收藏
页码:782 / 790
页数:9
相关论文
共 50 条
  • [1] Message-Passing Algorithms for Counting Short Cycles in a Graph
    Karimi, Mehdi
    Banihashemi, Amir H.
    [J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2013, 61 (02) : 485 - 495
  • [2] Message-Passing Algorithms: Reparameterizations and Splittings
    Ruozzi, Nicholas
    Tatikonda, Sekhar
    [J]. IEEE TRANSACTIONS ON INFORMATION THEORY, 2013, 59 (09) : 5860 - 5881
  • [3] Message-passing algorithms for quadratic minimization
    Ruozzi, Nicholas
    Tatikonda, Sekhar
    [J]. Journal of Machine Learning Research, 2013, 14 : 2287 - 2314
  • [4] Message-Passing Algorithms for Quadratic Minimization
    Ruozzi, Nicholas
    Tatikonda, Sekhar
    [J]. JOURNAL OF MACHINE LEARNING RESEARCH, 2013, 14 : 2287 - 2314
  • [5] Message-passing algorithms for compressed sensing
    Donoho, David L.
    Maleki, Arian
    Montanari, Andrea
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (45) : 18914 - 18919
  • [6] Polarized message-passing in graph neural networks
    He, Tiantian
    Liu, Yang
    Ong, Yew-Soon
    Wu, Xiaohu
    Luo, Xin
    [J]. ARTIFICIAL INTELLIGENCE, 2024, 331
  • [7] Hierarchical message-passing graph neural networks
    Zhong, Zhiqiang
    Li, Cheng-Te
    Pang, Jun
    [J]. DATA MINING AND KNOWLEDGE DISCOVERY, 2023, 37 (01) : 381 - 408
  • [8] Hierarchical message-passing graph neural networks
    Zhiqiang Zhong
    Cheng-Te Li
    Jun Pang
    [J]. Data Mining and Knowledge Discovery, 2023, 37 : 381 - 408
  • [9] Message-Passing Algorithms for the Verification of Distributed Protocols
    Jezequel, Loig
    Esparza, Javier
    [J]. VERIFICATION, MODEL CHECKING, AND ABSTRACT INTERPRETATION: (VMCAI 2014), 2014, 8318 : 222 - 241
  • [10] Message-Passing Algorithms and Improved LP Decoding
    Arora, Sanjeev
    Daskalakis, Constantinos
    Steurer, David
    [J]. STOC'09: PROCEEDINGS OF THE 2009 ACM SYMPOSIUM ON THEORY OF COMPUTING, 2009, : 3 - 12