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

Zhou, Wei LU and Lentmaier, Michael LU (2019) 12th International ITG Conference on Systems, Communications and Coding
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:
author
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
LDPC codes, Iterative Decoding, Generalized Min Sum
conference name
12th International ITG Conference on Systems, Communications and Coding
conference location
Rostock, Germany
conference dates
2019-02-11 - 2019-02-14
language
English
LU publication?
yes
id
e828fa4c-d25c-4363-9357-54f30c198288
date added to LUP
2019-03-07 17:52:58
date last changed
2019-04-04 10:11:03
@misc{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},
  keyword      = {LDPC codes,Iterative Decoding,Generalized Min Sum},
  language     = {eng},
  location     = {Rostock, Germany},
  title        = {Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding},
  year         = {2019},
}