Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

Wei Zhou; Michael Lentmaier

doi:10.30420/454862047

Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

Wei Zhou, Michael Lentmaier

Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review

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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.

Originalspråk	engelska
Titel på värdpublikation	SCC 2019 - 12th International ITG Conference on Systems, Communications and Coding
Förlag	VDE Verlag gmbh Berlin
Sidor	274-279
ISBN (elektroniskt)	978-3-8007-4862-4
ISBN (tryckt)	978-3-8007-4898-3
DOI	https://doi.org/10.30420/454862047
Status	Published - 2019
Evenemang	12th International ITG Conference on Systems, Communications and Coding - Rostock Univeristy, Rostock, Tyskland Varaktighet: 2019 feb. 11 → 2019 feb. 14 https://www.scc2019.net/

Konferens

Konferens	12th International ITG Conference on Systems, Communications and Coding
Förkortad titel	SCC
Land/Territorium	Tyskland
Ort	Rostock
Period	2019/02/11 → 2019/02/14
Internetadress	https://www.scc2019.net/

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@inproceedings{e828fa4cd25c4363935754f30c198288,

title = "Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding",

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 it is robust against LLR mismatch. ",

keywords = "LDPC codes, Iterative Decoding, Generalized Min Sum",

author = "Wei Zhou and Michael Lentmaier",

year = "2019",

doi = "10.30420/454862047",

language = "English",

isbn = "978-3-8007-4898-3",

pages = "274--279",

booktitle = "SCC 2019 - 12th International ITG Conference on Systems, Communications and Coding",

publisher = "VDE Verlag gmbh Berlin",

note = "12th International ITG Conference on Systems, Communications and Coding, SCC ; Conference date: 11-02-2019 Through 14-02-2019",

url = "https://www.scc2019.net/",

}

Zhou, W & Lentmaier, M 2019, Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding. i SCC 2019 - 12th International ITG Conference on Systems, Communications and Coding., S8-3, VDE Verlag gmbh Berlin, s. 274-279, 12th International ITG Conference on Systems, Communications and Coding, Rostock, Tyskland, 2019/02/11. https://doi.org/10.30420/454862047

TY - GEN

T1 - Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

AU - Zhou, Wei

AU - Lentmaier, Michael

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - LDPC codes

KW - Iterative Decoding

KW - Generalized Min Sum

UR - https://www.scopus.com/pages/publications/85099484519

U2 - 10.30420/454862047

DO - 10.30420/454862047

M3 - Paper in conference proceeding

SN - 978-3-8007-4898-3

SP - 274

EP - 279

BT - SCC 2019 - 12th International ITG Conference on Systems, Communications and Coding

PB - VDE Verlag gmbh Berlin

T2 - 12th International ITG Conference on Systems, Communications and Coding

Y2 - 11 February 2019 through 14 February 2019

ER -

Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

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