Error correction code is a major part of the physical communication layer, ensuring the
reliable transfer of data over noisy channels. Recently, neural decoders were shown to …

Error correction code (ECC) is an integral part of the physical communication layer, ensuring
reliable data transfer over noisy channels. Recently, neural decoders have demonstrated …

Neural networks can efficiently encode the probability distribution of errors in an error
correcting code. Moreover, these distributions can be conditioned on the syndromes of the …

We present a novel framework for applying deep neural networks (DNN) to soft decoding of
linear codes at arbitrary block lengths. Unlike other approaches, our framework allows …

For reliable transmission across a noisy communication channel, classical results from
information theory show that it is asymptotically optimal to separate out the source and …

There have been significant research activities in recent years to automate the design of
channel encoders and decoders via deep learning. Due the dimensionality challenge in …

High quality data is essential in deep learning to train a robust model. While in other fields
data is sparse and costly to collect, in error decoding it is free to query and label thus …

Standard decoding approaches rely on model-based channel estimation methods to
compensate for varying channel effects, which degrade in performance whenever there is a …

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) …

Coding theory is a central discipline underpinning wireline and wireless modems that are
the workhorses of the information age. Progress in coding theory is largely driven by …