Generalized LDPC Codes with Convolutional Code Constraints
(2020) 2020 IEEE International Symposium on Information Theory, ISIT 2020 p.479-484- Abstract
- Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes that can be described by a (2), (3)-regular compact graph. In this paper, we introduce a family of (d v , d c )-regular GLDPC codes with convolutional code constraints (CC-GLDPC codes), which form an extension of classical BCCs to arbitrary regular graphs. In order to characterize the performance in the waterfall and error floor regions, we perform an analysis of the density evolution thresholds as well as the finite-length ensemble weight enumerators and minimum distances of the ensembles. In particular, we consider various ensembles of overall rate R = 1/3 and R = 1/2 and study the trade-off between variable node degree and strength of the component... (More)
- Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes that can be described by a (2), (3)-regular compact graph. In this paper, we introduce a family of (d v , d c )-regular GLDPC codes with convolutional code constraints (CC-GLDPC codes), which form an extension of classical BCCs to arbitrary regular graphs. In order to characterize the performance in the waterfall and error floor regions, we perform an analysis of the density evolution thresholds as well as the finite-length ensemble weight enumerators and minimum distances of the ensembles. In particular, we consider various ensembles of overall rate R = 1/3 and R = 1/2 and study the trade-off between variable node degree and strength of the component codes. We also compare the results to corresponding classical LDPC codes with equal degrees and rates. It is observed that for the considered LDPC codes with variable node degree d v > 2, we can find a CC-GLDPC code with smaller d v that offers similar or better performance in terms of BP and MAP thresholds at the expense of a negligible loss in the minimum distance. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/01dcb0fe-35aa-4775-adc4-4a2f7252d0c8
- author
- Farooq, M. U. LU ; Moloudi, S. and Lentmaier, M. LU
- organization
- publishing date
- 2020-08-24
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2020 IEEE International Symposium on Information Theory (ISIT)
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 2020 IEEE International Symposium on Information Theory, ISIT 2020
- conference location
- Los Angeles, CA, United States
- conference dates
- 2020-06-21 - 2020-06-26
- external identifiers
-
- scopus:85090403387
- ISBN
- 978-1-7281-6432-8
- 978-1-7281-6433-5
- DOI
- 10.1109/ISIT44484.2020.9174017
- language
- English
- LU publication?
- yes
- id
- 01dcb0fe-35aa-4775-adc4-4a2f7252d0c8
- date added to LUP
- 2020-10-04 15:29:57
- date last changed
- 2024-08-08 02:03:49
@inproceedings{01dcb0fe-35aa-4775-adc4-4a2f7252d0c8, abstract = {{Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes that can be described by a (2), (3)-regular compact graph. In this paper, we introduce a family of (d v , d c )-regular GLDPC codes with convolutional code constraints (CC-GLDPC codes), which form an extension of classical BCCs to arbitrary regular graphs. In order to characterize the performance in the waterfall and error floor regions, we perform an analysis of the density evolution thresholds as well as the finite-length ensemble weight enumerators and minimum distances of the ensembles. In particular, we consider various ensembles of overall rate R = 1/3 and R = 1/2 and study the trade-off between variable node degree and strength of the component codes. We also compare the results to corresponding classical LDPC codes with equal degrees and rates. It is observed that for the considered LDPC codes with variable node degree d v > 2, we can find a CC-GLDPC code with smaller d v that offers similar or better performance in terms of BP and MAP thresholds at the expense of a negligible loss in the minimum distance.}}, author = {{Farooq, M. U. and Moloudi, S. and Lentmaier, M.}}, booktitle = {{2020 IEEE International Symposium on Information Theory (ISIT)}}, isbn = {{978-1-7281-6432-8}}, language = {{eng}}, month = {{08}}, pages = {{479--484}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Generalized LDPC Codes with Convolutional Code Constraints}}, url = {{http://dx.doi.org/10.1109/ISIT44484.2020.9174017}}, doi = {{10.1109/ISIT44484.2020.9174017}}, year = {{2020}}, }