Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding
(2019) 12th International ITG Conference on Systems, Communications and Coding p.274-279- Abstract
- The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).
In this work we propose a new algorithm, ga-min*, that generalizes the MS and a-min* in terms of number of incoming messages to a CN.
We analyze and demonstrate a condition to improve the performance when applying self-correction to the ga-min*.
Simulations on 5G LDPC codes show that the proposed decoding algorithm yields comparable performance to the a-min* with a significant reduction in complexity, and... (More) - The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).
In this work we propose a new algorithm, ga-min*, that generalizes the MS and a-min* in terms of number of incoming messages to a CN.
We analyze and demonstrate a condition to improve the performance when applying self-correction to the ga-min*.
Simulations on 5G LDPC codes show that the proposed decoding algorithm yields comparable performance to the a-min* with a significant reduction in complexity, and it is robust against LLR mismatch. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/e828fa4c-d25c-4363-9357-54f30c198288
- author
- Zhou, Wei LU and Lentmaier, Michael LU
- organization
- publishing date
- 2019
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- LDPC codes, Iterative Decoding, Generalized Min Sum
- host publication
- SCC 2019 - 12th International ITG Conference on Systems, Communications and Coding
- article number
- S8-3
- pages
- 274 - 279
- publisher
- VDE Verlag gmbh Berlin
- conference name
- 12th International ITG Conference on Systems, Communications and Coding
- conference location
- Rostock, Germany
- conference dates
- 2019-02-11 - 2019-02-14
- external identifiers
-
- scopus:85099484519
- ISBN
- 978-3-8007-4862-4
- 978-3-8007-4898-3
- DOI
- 10.30420/454862047
- language
- English
- LU publication?
- yes
- id
- e828fa4c-d25c-4363-9357-54f30c198288
- date added to LUP
- 2019-03-07 17:52:58
- date last changed
- 2024-08-22 14:19:15
@inproceedings{e828fa4c-d25c-4363-9357-54f30c198288, abstract = {{The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).<br/>In this work we propose a new algorithm, ga-min*, that generalizes the MS and a-min* in terms of number of incoming messages to a CN.<br/>We analyze and demonstrate a condition to improve the performance when applying self-correction to the ga-min*. <br/>Simulations on 5G LDPC codes show that the proposed decoding algorithm yields comparable performance to the a-min* with a significant reduction in complexity, and it is robust against LLR mismatch.}}, author = {{Zhou, Wei and Lentmaier, Michael}}, booktitle = {{SCC 2019 - 12th International ITG Conference on Systems, Communications and Coding}}, isbn = {{978-3-8007-4862-4}}, keywords = {{LDPC codes; Iterative Decoding; Generalized Min Sum}}, language = {{eng}}, pages = {{274--279}}, publisher = {{VDE Verlag gmbh Berlin}}, title = {{Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding}}, url = {{https://lup.lub.lu.se/search/files/90695124/document_12_18.pdf}}, doi = {{10.30420/454862047}}, year = {{2019}}, }