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The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.

Low-density parity-check codes based on finite geometries: a rediscovery and new results

Kou, Y., Lin, S., Fossorier, M.P.C.·2001·IEEE Transactions on Information Theory

Abstract

This paper presents a geometric approach to the construction of low-density parity-check (LDPC) codes. Four classes of LDPC codes are constructed based on the lines and points of Euclidean and projective geometries over finite fields. Codes of these four classes have good minimum distances and their Tanner (1981) graphs have girth 6. Finite-geometry LDPC codes can be decoded in various ways, ranging from low to high decoding complexity and from reasonably good to very good performance. They perform very well with iterative decoding. Furthermore, they can be put in either cyclic or quasi-cyclic form. Consequently, their encoding can be achieved in linear time and implemented with simple feedback shift registers. This advantage is not shared by other LDPC codes in general and is important in practice. Finite-geometry LDPC codes can be extended and shortened in various ways to obtain other good LDPC codes. Several techniques of extension and shortening are presented. Long extended finite-geometry LDPC codes have been constructed and they achieve a performance only a few tenths of a decibel away from the Shannon theoretical limit with iterative decoding.

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Metadata

Authors
Kou, Y., Lin, S., & Fossorier, M. P. C.
Venue
IEEE Transactions on Information Theory
Published
2001
Volume
47
Issue
7
Pages
2711-2736
ISSN
0018-9448 (ISSN-L)
OpenAlex
W2114869758
Cited by
1,302
References
42
FWCI
57.15
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Low-density parity-check codes based on finite geometries: a rediscovery and new results. https://app.cochat.ai/papers/10.1109/18.959255
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Kou, Y., Lin, S., & Fossorier, M. P. C. (2001). Low-density parity-check codes based on finite geometries: a rediscovery and new results. IEEE Transactions on Information Theory. https://doi.org/10.1109/18.959255

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