Channel coding plays a pivotal role in ensuring reliable communication over wireless
channels. With the growing need for ultra-reliable communication in emerging wireless use …

The success of deep learning has encouraged its applications in decoding error-correcting
codes, eg, LDPC decoding. In this paper, we propose a model-driven deep learning method …

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 …

With the rapid development of smart grids, the deployment number of transmission lines has
significantly increased, posing significant challenges to the detection and maintenance of …

In this paper, we propose low complexity joint-way compression algorithms with Tensor-
Ring (TR) decomposition and weight sharing to further lower the storage and computational …

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 …

Practical wiretap code design for reliable and confidential communication is a difficult multi-
objective task. In literature, neural networks (NN) have been designed as channel encoders …

It is known the belief propagation variants of linear codes can be readily unrolled as neural
networks, after assigning learnable weights on the message‐passing edges. Contrary to the …

The Consultative Committee for Space Data Systems (CCSDS) 141.11-O-1 Line Product
Code (LPC) provides a rare opportunity to compare maximum-likelihood decoding and …

Ultra‐reliable low‐latency communications, URLLC, are designed for applications such as
self‐driving cars and telesurgery requiring a response in milliseconds and are very sensitive …