Deep Learning for Decoding of Linear Codes - A Syndrome-Based Approach

Keywords

Decoding methods, Computer science, Overfitting, Generalization, Preprocessor

References

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• Deep Learning Methods for Improved Decoding of Linear CodesEliya Nachmani, Elad Marciano, Loren Lugosch — 2017
• An Introduction to Deep Learning for the Physical LayerTimothy J. O’Shea, Jakob Hoydis — 2017
• Near Maximum Likelihood Decoding with Deep LearningEliya Nachmani, Yaron Bachar, Elad Marciano — 2018
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Cited by

• Decoding Optimization for 5G LDPC Codes by Machine LearningXiaoning Wu, Ming Jiang, Chunming Zhao — 2018
• Learning from the SyndromeLoren Lugosch, Warren J. Gross — 2018
• What Can Machine Learning Teach Us about Communications?Mengke Lian, Christian Häger, Henry D. Pfister — 2018
• Neural Decoder for Topological Codes using Pseudo-Inverse of Parity Check MatrixChaitanya Chinni, Abhishek Kulkarni, Dheeraj M. Pai — 2019
• Simplified Deep-Learning-based decoders for linear block codesE. Kavvousanos, Vassilis Paliouras, Ioannis Kouretas — 2018
• Deep Learning Based Joint Detection and Decoding of Non-Orthogonal Multiple Access SystemsFuqiang Sun, Kai Niu, Chao Dong — 2018
• Optimal Training Channel Statistics for Neural-based DecodersMeryem Benammar, Pablo Piantanida — 2018
• Neural net decoders of binary codesV V Butov, V. N. Dumachev — 2019
• Deep Learning-Constructed Joint Transmission-Recognition for Internet of ThingsChia‐Han Lee, Jia-Wei Lin, Po-Hao Chen — 2019
• Active Deep Decoding of Linear CodesIshay Be’ery, Nir Raviv, Tomer Raviv — 2019
• Reinforcement Learning for Channel Coding: Learned Bit-Flipping DecodingFabrizio Carpi, Christian Häger, Marco Martalò — 2019
• Learned Belief-Propagation Decoding with Simple Scaling and SNR AdaptationMengke Lian, Fabrizio Carpi, Christian Häger — 2019
• Offset min-sum Optimization for General Decoding Scheduling: A Deep Learning ApproachAhmed Attia Abotabl, Jung Hyun Bae, Kee-Bong Song — 2019
• Hardware Implementation Aspects of a Syndrome-based Neural Network Decoder for BCH CodesE. Kavvousanos, Vassilis Paliouras — 2019
• perm2vec: Graph Permutation Selection for Decoding of Error Correction Codes using Self-AttentionAvi Caciularu, Nir Raviv, Tomer Raviv — 2020
• Belief Propagation with Deep Unfolding for High-dimensional Inference in Communication SystemsMengke Lian — 2019
• Deep Learning Assisted Sum-Product Detection Algorithm for Faster-than-Nyquist SignalingBryan Liu, Shuangyang Li, Yixuan Xie — 2019
• Low-Latency Neural Decoders for Linear and Non-Linear Block CodesCheuk Ting Leung, Rajshekhar Vishweshwar Bhat, Mehul Motani — 2019
• ATRNN: Using Seq2Seq Approach for Decoding Polar CodesAniket Dhok, Swapnil Bhole — 2020
• Receiver Design for Faster-Than-Nyquist Signaling: Deep-Learning-Based ArchitecturesPeiyang Song, Fengkui Gong, Qiang Li — 2018

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