This paper provides a comprehensive survey of recent advances in deep learning (DL)
techniques for channel coding problems. Inspired by the recent successes of DL in a variety …

This paper focuses on the design of high-performance polar codes with dynamic frozen bits
that can be compactly specified. We split the code design problem into the frozen set design …

Polarization-adjusted convolutional (PAC) codes combine polar and convolutional
transformations to enhance the distance properties of polar codes. They offer a performance …

Polarization-adjusted convolutional (PAC) codes of short blocklengths over the binary-input
additive white Gaussian noise channel have excellent performance. To further improve the …

Despite the extreme error-correction performance, the amount of computation of sequential
decoding of the polarization-adjusted convolutional (PAC) codes is random. In sequential …

Polar codes are the first class of structured channel codes that achieve the symmetric
capacity of binary channels with efficient encoding and decoding. In 2019, Arikan proposed …

A novel rate-profiling design is proposed for polarization-adjusted convolutional (PAC)
codes under list decoding, adopting a path probability perspective. Inspired by the concepts …

We study the performance of sequential decoding of polarization-adjusted con-volutional
(PAC) codes. We present a metric function that employs bit-channel mutual information and …

In this paper, we introduce a novel rate-profile design based on search-constrained
optimization techniques to assess the performance of polarization-adjusted convolutional …

In this paper, we propose some new constraints on the rate profile based on the reliability of
the bit-channels to optimize the polarization-adjusted convolutional (PAC) codes under …