Deep learning methods for improved decoding of linear codes
E Nachmani, E Marciano, L Lugosch… - IEEE Journal of …, 2018 - ieeexplore.ieee.org
The problem of low complexity, close to optimal, channel decoding of linear codes with short
to moderate block length is considered. It is shown that deep learning methods can be used …
to moderate block length is considered. It is shown that deep learning methods can be used …
Learning to decode linear codes using deep learning
E Nachmani, Y Be'ery… - 2016 54th Annual Allerton …, 2016 - ieeexplore.ieee.org
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 method generalizes the standard belief propagation algorithm by assigning weights to …
Performance analysis of linear codes under maximum-likelihood decoding: A tutorial
This article is focused on the performance evaluation of linear codes under optimal
maximum-likelihood (ML) decoding. Though the ML decoding algorithm is prohibitively …
maximum-likelihood (ML) decoding. Though the ML decoding algorithm is prohibitively …
RNN decoding of linear block codes
E Nachmani, E Marciano, D Burshtein… - arXiv preprint arXiv …, 2017 - arxiv.org
Designing a practical, low complexity, close to optimal, channel decoder for powerful
algebraic codes with short to moderate block length is an open research problem. Recently …
algebraic codes with short to moderate block length is an open research problem. Recently …
Pruning and quantizing neural belief propagation decoders
A Buchberger, C Häger, HD Pfister… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
We consider near maximum-likelihood (ML) decoding of short linear block codes. In
particular, we propose a novel decoding approach based on neural belief propagation …
particular, we propose a novel decoding approach based on neural belief propagation …
Refined belief propagation decoding of sparse-graph quantum codes
Quantum stabilizer codes constructed from sparse matrices have good performance and can
be efficiently decoded by belief propagation (BP). A conventional BP decoding algorithm …
be efficiently decoded by belief propagation (BP). A conventional BP decoding algorithm …
Pruning neural belief propagation decoders
A Buchberger, C Häger, HD Pfister… - 2020 IEEE …, 2020 - ieeexplore.ieee.org
We consider near maximum-likelihood (ML) decoding of short linear block codes based on
neural belief propagation (BP) decoding recently introduced by Nachmani et al.. While this …
neural belief propagation (BP) decoding recently introduced by Nachmani et al.. While this …
Learning from the syndrome
In this paper, we introduce the syndrome loss, an alternative loss function for neural error-
correcting decoders based on a relaxation of the syndrome. The syndrome loss penalizes …
correcting decoders based on a relaxation of the syndrome. The syndrome loss penalizes …
Log-domain decoding of quantum LDPC codes over binary finite fields
A quantum stabilizer code over corresponds to a classical additive code over that is self-
orthogonal with respect to a symplectic inner product. We study the decoding of quantum …
orthogonal with respect to a symplectic inner product. We study the decoding of quantum …
Decoding Reed-Muller codes using minimum-weight parity checks
Reed-Muller (RM) codes exhibit good performance under maximum-likelihood (ML)
decoding due to their highly-symmetric structure. In this paper, we explore the question of …
decoding due to their highly-symmetric structure. In this paper, we explore the question of …