Deep learning based physical layer security for terrestrial communications in 5G and beyond networks: A survey
The key principle of physical layer security (PLS) is to permit the secure transmission of
confidential data using efficient signal-processing techniques. Also, deep learning (DL) has …
confidential data using efficient signal-processing techniques. Also, deep learning (DL) has …
Designing finite alphabet iterative decoders of LDPC codes via recurrent quantized neural networks
In this paper, we propose a new approach to design finite alphabet iterative decoders
(FAIDs) for Low-Density Parity Check (LDPC) codes over binary symmetric channel (BSC) …
(FAIDs) for Low-Density Parity Check (LDPC) codes over binary symmetric channel (BSC) …
Neural-network-optimized degree-specific weights for ldpc minsum decoding
Neural Normalized MinSum (N-NMS) decoding delivers better frame error rate (FER)
performance on linear block codes than conventional normalized MinSum (NMS) by …
performance on linear block codes than conventional normalized MinSum (NMS) by …
Reconstruction-computation-quantization (RCQ): A paradigm for low bit width LDPC decoding
This paper uses the reconstruction-computation-quantization (RCQ) paradigm to decode
low-density parity-check (LDPC) codes. RCQ facilitates dynamic non-uniform quantization to …
low-density parity-check (LDPC) codes. RCQ facilitates dynamic non-uniform quantization to …
Recent Advances in Deep Learning for Channel Coding: A Survey
T Matsumine, H Ochiai - arXiv preprint arXiv:2406.19664, 2024 - arxiv.org
This paper provides a comprehensive survey on recent advances in deep learning (DL)
techniques for the channel coding problems. Inspired by the recent successes of DL in a …
techniques for the channel coding problems. Inspired by the recent successes of DL in a …
Optimized Non-Surjective FAIDs for 5G LDPC Codes With Learnable Quantization
Y Lyu, M Jiang, Y Zhang, C Zhao… - IEEE Communications …, 2023 - ieeexplore.ieee.org
This letter proposes a novel approach for designing non-surjective (NS) finite alphabet
iterative decoders (FAIDs) for quasi-cyclic low-density parity-check (LDPC) codes, especially …
iterative decoders (FAIDs) for quasi-cyclic low-density parity-check (LDPC) codes, especially …
LDPC Decoding with Degree-Specific Neural Message Weights and RCQ Decoding
L Wang, C Terrill, D Divsalar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, neural networks have improved MinSum message-passing decoders for low-
density parity-check (LDPC) codes by multiplying or adding weights to the messages, where …
density parity-check (LDPC) codes by multiplying or adding weights to the messages, where …
FAID diversity via neural networks
Decoder diversity is a powerful error correction framework in which a collection of decoders
collaboratively correct a set of error patterns otherwise uncorrectable by any individual …
collaboratively correct a set of error patterns otherwise uncorrectable by any individual …
Autoregressive belief propagation for decoding block codes
E Nachmani, L Wolf - arXiv preprint arXiv:2103.11780, 2021 - arxiv.org
We revisit recent methods that employ graph neural networks for decoding error correcting
codes and employ messages that are computed in an autoregressive manner. The outgoing …
codes and employ messages that are computed in an autoregressive manner. The outgoing …
Deep-learning for breaking the trapping sets in low-density parity-check codes
In the low-error rate regime, message-passing (MP) decoding for low-density parity-check
(LDPC) codes is known to have performance degradation due to trapping sets (TSs), which …
(LDPC) codes is known to have performance degradation due to trapping sets (TSs), which …