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IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences

MAP and LogMAP Decoding Algorithms for Linear Block Codes Using a Code Structure

Yuichi Kaji

Published Oct 25, 2000• 7 citations
OpenAlex

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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 endomor-phisms, 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.

arXiv:2402.00562•IEEE International Symposium on Information Theory (ISIT)•Jul 7, 2024•4 citations
A new algorithm for the LogMAP decoding of linear block codes is considered. The decoding complexity is evaluated analytically and by computer simulation. The proposed algorithm is an improvement of the recursive LogMAP algorithm proposed by the authors. The recursive LogMAP algorithm is more efficient than the BCJR algorithm for low-rate codes, but the complexity grows considerably large for high-rate codes. The aim of the proposed algorithm is to solve the complexity explosion of the recursive LogMAP algorithm for high-rate codes. The proposed algorithm is more efficient than the BCJR algorithm for well-known linear block codes.
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 endomor-phisms, 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.