Endomorphisms of Linear Block Codes

Jonathan Mandelbaum, Sisi Miao, Holger Jäkel, Laurent Schmalen
Computer Science, Information Theory, Information Theory (cs.IT)
2024-02-01 00:00:00
The automorphism groups of various linear codes are well-studied yielding valuable insights into the respective code structure. This knowledge is successfully applied 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.
PDF: Endomorphisms of Linear Block Codes.pdf
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