Constrained sequence (CS) codes, including fixed-length CS codes and variable-length CS
codes, have been widely used in modern wireless communication and data storage …

Designing channel codes under low-latency constraints is one of the most demanding
requirements in 5G standards. However, a sharp characterization of the performance of …

Error-correcting codes are very important in modern communication systems. In this paper,
we investigate efficient reduced-complexity deep neural network (DNN)-aided channel …

In this paper, we introduce a method of using quantized neural networks (QNN) to design
finite alphabet message passing decoders (FAID) for Low-Density Parity Check (LDPC) …

We consider the concatenation of a convolutional code (CC) with an optimized cyclic
redundancy check (CRC) code as a promising paradigm for good short blocklength codes …

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 …

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 …

We consider the design of efficient neural-network based algorithms, referred to as neural
decoders, for decoding linear and non-linear block codes, such as Hamming and constant …

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 …

Cyclic redundancy check (CRC) codes check if a codeword is correctly received. This paper
presents an algorithm to design CRC codes that are optimized for the code-specific error …