mlsanityData to 7 Oct 2026

Learning to Decode Linear Codes Using Deep Learning

arXiv 1607.04793 ↗First posted 16 Jul 2016cs.IT cs.LG cs.NEcited by 60

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Abstract (arXiv)

A novel deep learning method for improving the belief propagation algorithm is proposed. The method generalizes the standard belief propagation algorithm by assigning weights to the edges of the Tanner graph. These edges are then trained using deep learning techniques. A well-known property of the belief propagation algorithm is the independence of the performance on the transmitted codeword. A crucial property of our new method is that our decoder preserved this property. Furthermore, this property allows us to learn only a single codeword instead of exponential number of code-words. Improvements over the belief propagation algorithm are demonstrated for various high density parity check codes.

Key facts. Cited by 60 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jul 2016.

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Citing papers per year: 2021: 12; 2022: 15; 2023: 10; 2024: 11; 2025: 6; 2026: 6.

60 papers.

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  1. 2022Error Correction Code Transformercited by 47
  2. 2024CrossMPT: Cross-attention Message-Passing Transformer for Error Correcting Codescited by 20
  3. 2021KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learningcited by 16
  4. 2021Autoregressive Belief Propagation for Decoding Block Codescited by 15
  5. 2021ProductAE: Towards Training Larger Channel Codes based on Neural Product Codescited by 14
  6. 2021Cyclically Equivariant Neural Decoders for Cyclic Codescited by 12
  7. 2023Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issuescited by 12
  8. 2022Graph Neural Networks for Channel Decodingcited by 10
  9. 2023Deep Quantum Error Correctioncited by 10
  10. 2024Neural Active Learning Beyond Banditscited by 10
  11. 2022Low-complexity Near-optimum Symbol Detection Based on Neural Enhancement of Factor Graphscited by 8
  12. 2024Learning Linear Block Error Correction Codescited by 8
38 more
  1. 2021FAID Diversity via Neural Networkscited by 5
  2. 2022CRISP: Curriculum based Sequential Neural Decoders for Polar Code Familycited by 5
  3. 2023How to Mask in Error Correction Code Transformer: Systematic and Double Maskingcited by 5
  4. 2022Neural Decoding with Optimization of Node Activationscited by 4
  5. 2023Robust Non-Linear Feedback Coding via Power-Constrained Deep Learningcited by 4
  6. 2023Generalization Bounds for Neural Belief Propagation Decoderscited by 4
  7. 2024LightCode: Light Analytical and Neural Codes for Channels with Feedbackcited by 4
  8. 2025Hybrid Mamba-Transformer Decoder for Error-Correcting Codescited by 4
  9. 2021CMDNet: Learning a Probabilistic Relaxation of Discrete Variables for Soft Detection with Low Complexitycited by 3
  10. 2021Learning OFDM Waveforms with PAPR and ACLR Constraintscited by 3
  11. 2022Neural Enhancement of Factor Graph-based Symbol Detectioncited by 3
  12. 2022Interpreting Neural Min-Sum Decoderscited by 3
  13. 2022TinyTurbo: Efficient Turbo Decoders on Edgecited by 3
  14. 2024Accelerating Error Correction Code Transformerscited by 3
  15. 2024Nested Construction of Polar Codes via Transformerscited by 2
  16. 2025Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codescited by 2
  17. 2021Doubly Residual Neural Decoder: Towards Low-Complexity High-Performance Channel Decodingcited by 1
  18. 2021Improving the List Decoding Version of the Cyclically Equivariant Neural Decodercited by 1
  19. 2021List Autoencoder: Towards Deep Learning Based Reliable Transmission Over Noisy Channelscited by 1
  20. 2022Structural Optimization of Factor Graphs for Symbol Detection via Continuous Clustering and Machine Learningcited by 1
  21. 2022Optimizing Serially Concatenated Neural Codes with Classical Decoderscited by 1
  22. 2023ProductAE: Toward Deep Learning Driven Error-Correction Codes of Large Dimensionscited by 1
  23. 2023AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recoverycited by 1
  24. 2023Learning in Deep Factor Graphs with Gaussian Belief Propagationcited by 1
  25. 2024Friendly Attacks to Improve Channel Coding Reliabilitycited by 1
  26. 2024DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learningcited by 1
  27. 2024Factor Graph Optimization of Error-Correcting Codes for Belief Propagation Decodingcited by 1
  28. 2024Learning Robust Representations for Communications over Noisy Channelscited by 1
  29. 2025Transformer-Based Decoding in Concatenated Coding Schemes Under Synchronization Errorscited by 1
  30. 2026Generalization Bounds for Transformer Channel Decoderscited by 1
  31. 2021A Learning-Based Approach to Address Complexity-Reliability Tradeoff in OS Decoderscited by 0
  32. 2021Recovering AES Keys with a Deep Cold Boot Attackcited by 0
  33. 2022Channel model for end-to-end learning of communications systems: A surveycited by 0
  34. 2022A recipe of training neural network-based LDPC decoderscited by 0
  35. 2022Neural Network Decoders for Permutation Codes Correcting Different Errorscited by 0
  36. 2022Hybrid HMM Decoder For Convolutional Codes By Joint Trellis-Like Structure and Channel Priorcited by 0
  37. 2022A Scalable Graph Neural Network Decoder for Short Block Codescited by 0
  38. 2023Local Message Passing on Frustrated Systemscited by 0

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