PAC codes with Bounded-Complexity Sequential Decoding: Pareto Distribution and Code Design

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Main Authors: Moradi, Mohsen, Mahdavifar, Hessam
Format: Preprint
Published: 2024
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author Moradi, Mohsen
Mahdavifar, Hessam
author_facet Moradi, Mohsen
Mahdavifar, Hessam
contents Recently, a novel variation of polar codes known as polarization-adjusted convolutional (PAC) codes has been introduced by Arıkan. These codes significantly outperform conventional polar and convolutional codes, particularly for short codeword lengths, and are shown to operate very close to the optimal bounds. It has also been shown that if the rate profile of PAC codes does not adhere to certain polarized cutoff rate constraints, the computation complexity for their sequential decoding grows exponentially. In this paper, we address the converse problem, demonstrating that if the rate profile of a PAC code follows the polarized cutoff rate constraints, the required computations for its sequential decoding can be bounded with a distribution that follows a Pareto distribution. This serves as a guideline for the rate-profile design of PAC codes. For a high-rate PAC\,$(1024,899)$ code, simulation results show that the PAC code with Fano decoder, when constructed based on the polarized cutoff rate constraints, achieves a coding gain of more than $0.75$ dB at a frame error rate (FER) of $10^{-5}$ compared to the state-of-the-art 5G polar and LDPC codes.
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publishDate 2024
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spellingShingle PAC codes with Bounded-Complexity Sequential Decoding: Pareto Distribution and Code Design
Moradi, Mohsen
Mahdavifar, Hessam
Information Theory
Computational Complexity
Recently, a novel variation of polar codes known as polarization-adjusted convolutional (PAC) codes has been introduced by Arıkan. These codes significantly outperform conventional polar and convolutional codes, particularly for short codeword lengths, and are shown to operate very close to the optimal bounds. It has also been shown that if the rate profile of PAC codes does not adhere to certain polarized cutoff rate constraints, the computation complexity for their sequential decoding grows exponentially. In this paper, we address the converse problem, demonstrating that if the rate profile of a PAC code follows the polarized cutoff rate constraints, the required computations for its sequential decoding can be bounded with a distribution that follows a Pareto distribution. This serves as a guideline for the rate-profile design of PAC codes. For a high-rate PAC\,$(1024,899)$ code, simulation results show that the PAC code with Fano decoder, when constructed based on the polarized cutoff rate constraints, achieves a coding gain of more than $0.75$ dB at a frame error rate (FER) of $10^{-5}$ compared to the state-of-the-art 5G polar and LDPC codes.
title PAC codes with Bounded-Complexity Sequential Decoding: Pareto Distribution and Code Design
topic Information Theory
Computational Complexity
url https://arxiv.org/abs/2412.06072