Decoding Golay Codes and their Related Lattices: A PAC Code Perspective

πŸ“… 2026-02-02
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This work addresses the problem of efficient near-maximum-likelihood decoding for Golay codes and their associated lattices, such as the Leech lattice Ξ›β‚‚β‚„ and its main sublattice Hβ‚‚β‚„. The authors propose a parallel list decoding algorithm that integrates the conceptual framework of polarization-adjusted convolutional (PAC) codes with Forney’s cubic construction. This approach marks the first application of the PAC coding paradigm to Golay code decoding, eliminating the need for index permutations and codeword puncturing required in conventional methods. Consequently, the decoding process is significantly simplified while achieving enhanced parallelism. The proposed algorithm maintains performance close to maximum likelihood and naturally extends to high-dimensional lattice structures, thereby enabling a unified and efficient decoding strategy for both Golay codes and the Leech lattice.

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πŸ“ Abstract
In this work, we propose a decoding method of Golay codes from the perspective of Polarization Adjusted Convolutional (PAC) codes. By invoking Forney's cubing construction of Golay codes and their generators $G^*(8,7)/(8,4)$, we found different construction methods of Golay codes from PAC codes, which result in an efficient parallel list decoding algorithm with near-maximum likelihood performance. Compared with existing methods, our method can get rid of index permutation and codeword puncturing. Using the new decoding method, some related lattices, such as Leech lattice $\Lambda_{24}$ and its principal sublattice $H_{24}$, can be also decoded efficiently.
Problem

Research questions and friction points this paper is trying to address.

Golay codes
lattice decoding
Leech lattice
PAC codes
maximum likelihood decoding
Innovation

Methods, ideas, or system contributions that make the work stand out.

PAC codes
Golay codes
parallel list decoding
Leech lattice
Forney's cubing construction
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