Braided Convolutional Self-orthogonal Codes with Double Sliding Window Decoding

Min Zhu, Andrew D. Cummins, David G.M. Mitchell, Michael Lentmaier, Daniel J. Costello

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

Sammanfattning

In this paper, we investigate a class of braided convolutional codes (BCCs), where the component codes are convolutional self-orthogonal codes (CSOCs), called braided convolutional self-orthogonal codes. Compared to conventional BCCs, the advantages of braided CSOCs include the availability of several low-complexity decoding methods and the relative ease of extending these methods to high rates More specifically, to construct high-rate braided codes, it is necessary to use higher-rate component codes, which results in exponentially higher decoding complexity with conventional BCJR decoding, whereas the complexity of the CSOC decoding methods proposed here grows only linearly with rate. In particular, we introduce a double sliding window decoding method based on belief propagation (BP) for braided CSOCs, which exhibits good performance while maintaining low-complexity decoding for the higher rates required in many applications.

Originalspråkengelska
Titel på värdpublikation2023 12th International Symposium on Topics in Coding, ISTC 2023
FörlagIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (elektroniskt)9798350326116
DOI
StatusPublished - 2023
Evenemang12th International Symposium on Topics in Coding, ISTC 2023 - Brest, Frankrike
Varaktighet: 2023 sep. 42023 sep. 8

Konferens

Konferens12th International Symposium on Topics in Coding, ISTC 2023
Land/TerritoriumFrankrike
OrtBrest
Period2023/09/042023/09/08

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