Polar codes have attracted the attention of academia and industry alike in the past decade,
such that the 5th generation wireless systems (5G) standardization process of the 3rd …

The training complexity of deep learning-based channel decoders scales exponentially with
the codebook size and therefore with the number of information bits. Thus, neural network …

We propose a belief propagation list (BPL) decoder with comparable performance to the
successive cancellation list (SCL) decoder of polar codes, which already achieves the …

An extension of polar codes is proposed, which allows some of the frozen symbols, called
dynamic frozen symbols, to be data-dependent. A construction of polar codes with dynamic …

We present a new framework for constructing polar codes (ie, selecting the frozen bit
positions) for arbitrary channels, tailored to a given decoding algorithm rather than assuming …

We show that the performance of iterative belief propagation (BP) decoding of polar codes
can be enhanced by decoding over different carefully chosen factor graph realizations. With …

Although iterative decoding of polar codes has recently made huge progress based on the
idea of permuted factor graphs, it still suffers from a non-negligible performance degradation …

Polar codes are the first class of error correcting codes that provably achieve the channel
capacity at infinite code length. They were selected for use in the fifth generation of cellular …

An optimization algorithm for finding a shortening pattern and a set of frozen symbols for
polar codes is proposed. The structure of polar codes is exploited to eliminate many …

This paper presents deep learning (DL) methods to optimize polar belief propagation (BP)
decoding and concatenated LDPC-polar codes. First, two-dimensional offset Min-Sum (2-D …