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arXiv 2402.00562cs.ITmath.IT
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线性分组码的自同态

Endomorphisms of Linear Block Codes

Jonathan Mandelbaum, Sisi Miao, Holger Jäkel, Laurent Schmalen

AI总结:

该研究探讨线性分组码自同态变换矩阵的结构,构建相关双射与一一映射以辅助自同态搜索,提出基于自同构获取未知自同态的方法,并验证自同态集成译码可在其他方案不适用时提升译码性能。

摘要:

各类线性码的自同构群已得到广泛研究,为揭示相应码的结构提供了洞见。这类知识可应用于理论分析、提升译码性能等场景,这也推动了对线性码自同态的研究。本工作探讨了码自同态的变换矩阵集合的结构——码自同态被定义为码自同构的推广,并明确构造了自同态的像与其典范商空间之间的双射映射。此外,我们在自同态变换矩阵集合与一个更大的线性分组码之间建立了一一映射,使得可使用成熟算法搜索合适的自同态。我们还提出了一种基于码的自同构获取未知码自同态的方法。另外,我们通过引入自同态集成译码(EED),将集成译码视为自同态的一个潜在用例。值得注意的是,当其他集成译码方案不适用时,EED仍可提升译码性能。

英文摘要:

The automorphism groups of various linear codes are extensively studied yielding insights into the respective code structure. This knowledge is used in, e.g., theoretical analysis and in improving decoding performance, motivating the analyses of endomorphisms of linear codes. In this work, we discuss the structure of the set of transformation matrices of code endomorphisms, defined as a generalization of code automorphisms, and provide an explicit construction of a bijective mapping between the image of an endomorphism and its canonical quotient space. Furthermore, we introduce a one-to-one mapping between the set of transformation matrices of endomorphisms and a larger linear block code enabling the use of well-known algorithms for the search for suitable endomorphisms. Additionally, we propose an approach to obtain unknown code endomorphisms based on automorphisms of the code. Furthermore, we consider ensemble decoding as a possible use case for endomorphisms by introducing endomorphism ensemble decoding. Interestingly, EED can improve decoding performance when other ensemble decoding schemes are not applicable.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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