Braided Convolutional Self-orthogonal Codes with Double Sliding Window Decoding
(2023) 12th International Symposium on Topics in Coding, ISTC 2023- Abstract
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... (More)
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.
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- author
- Zhu, Min ; Cummins, Andrew D. ; Mitchell, David G.M. ; Lentmaier, Michael LU and Costello, Daniel J.
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Braided convolutional codes, convolutional self-orthogonal codes, sliding window decoding, threshold decoding
- host publication
- 2023 12th International Symposium on Topics in Coding, ISTC 2023
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 12th International Symposium on Topics in Coding, ISTC 2023
- conference location
- Brest, France
- conference dates
- 2023-09-04 - 2023-09-08
- external identifiers
-
- scopus:85174607191
- ISBN
- 9798350326116
- DOI
- 10.1109/ISTC57237.2023.10273524
- language
- English
- LU publication?
- yes
- id
- 47b17633-5a95-48f2-bae5-65f16a8de52e
- date added to LUP
- 2023-12-18 12:22:51
- date last changed
- 2024-02-09 11:01:53
@inproceedings{47b17633-5a95-48f2-bae5-65f16a8de52e, abstract = {{<p>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.</p>}}, author = {{Zhu, Min and Cummins, Andrew D. and Mitchell, David G.M. and Lentmaier, Michael and Costello, Daniel J.}}, booktitle = {{2023 12th International Symposium on Topics in Coding, ISTC 2023}}, isbn = {{9798350326116}}, keywords = {{Braided convolutional codes; convolutional self-orthogonal codes; sliding window decoding; threshold decoding}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Braided Convolutional Self-orthogonal Codes with Double Sliding Window Decoding}}, url = {{http://dx.doi.org/10.1109/ISTC57237.2023.10273524}}, doi = {{10.1109/ISTC57237.2023.10273524}}, year = {{2023}}, }