Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Advances in intelligent and soft computing

Improved BP-Based Decoding Algorithms Integrated with GA for LDPC Codes

Zerong Deng, Xingcheng Liu

Published Jan 1, 2009• 2 citations
Publisher
DOI
10.1007/978-3-642-03664-4_78

Related papers

Design and Evaluation of LDPC Code Decoder Using Generalized BP Algorithm

Hashimoto Akiyoshi, Morino Harumi

IEICE Technical Report; IEICE Tech. Rep.•May 14, 2015•0 citations

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

Wei Zhou, Michael Lentmaier

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.

Systems Communications•Jan 1, 2019•7 citations

Modified BP Decoding Algorithms Combined with GA for Low-Density Parity Check Codes

Zerong Deng, Xingcheng Liu, Man Teng

In this paper we propose algorithms which combine Belief-propagation (BP) decoding algorithm with genetic algorithm (GA). The main idea is to improve the performance of traditional BP decoding algorithm by efficiently using the belief of variable nodes passing to check nodes. By considering the belief as genes, the proposed algorithms mainly employ the mutation operation in GA, and change the genes¿ amplitudes (either increase or decrease) when updating the check nodes¿ information. First, we explore that the marriage of the GA and BP decoding algorithm is reasonable. Three algorithms are proposed accordingly. Proposed algorithm I mutates chosen genes by amplitude enhancement, while proposed algorithm II by amplitude reduction. Finally, proposed algorithm III is a mixture of the former two. From computer simulation results, we show that for short and middle length LDPC codes, our proposed algorithms can improve both BER (bit error rate) and FER (frame error rate) performance over traditional BP decoding algorithm, with slight modification of traditional BP decoding algorithm and little increase of computation complexity.

International Conference on Computational Intelligence and Security (CIS)•Dec 1, 2008•6 citations

An Improvement of Layered BP Decoding Algorithm for Rate-Compatible Punctured LDPC Codes

Gou Hosoya, Hideki Yagi, Manabu Kobayashi

IEICE Technical Report; IEICE Tech. Rep.•Jan 11, 2011•0 citations

New interative decoding algorithms for low-density parity-check (LDPC) codes

Nastaran Mobini

•Jan 1, 2011•0 citations

An improved UMP BP-based decoding algorithm for irregular LDPC codes

Chuan Zhang

In order to reduce the performance loss of UMP BP-based decoding algorithm relative to LLR-BP decoding algorithm,an improved UMP BP-based decoding algorithm is proposed.When the check nodes process the message,the normalized BP-based decoding algorithm and offset BP-based decoding algorithm are integrated effectively by setting a correction factor and an offset factor reasonably.When the variable nodes process the message,an oscillation compensation algorithm based on LLR-BP decoding algorithm is introduced.Simulation results show that based on the irregular LDPC codes and under the condition of the same bit error rate within a certain range,the improved UMP BP-based decoding algorithm improves the decoding performance greatly compared with the three decoding algorithms which are based on UMP BP,normalized BP and offset BP decoding algorithms,respectively,and therefore quite efficiently approaches to the LLR-BP decoding algorithm which has excellent performance.

Applied science and technology•Jan 1, 2010•1 citation
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.
In this paper we propose algorithms which combine Belief-propagation (BP) decoding algorithm with genetic algorithm (GA). The main idea is to improve the performance of traditional BP decoding algorithm by efficiently using the belief of variable nodes passing to check nodes. By considering the belief as genes, the proposed algorithms mainly employ the mutation operation in GA, and change the genes¿ amplitudes (either increase or decrease) when updating the check nodes¿ information. First, we explore that the marriage of the GA and BP decoding algorithm is reasonable. Three algorithms are proposed accordingly. Proposed algorithm I mutates chosen genes by amplitude enhancement, while proposed algorithm II by amplitude reduction. Finally, proposed algorithm III is a mixture of the former two. From computer simulation results, we show that for short and middle length LDPC codes, our proposed algorithms can improve both BER (bit error rate) and FER (frame error rate) performance over traditional BP decoding algorithm, with slight modification of traditional BP decoding algorithm and little increase of computation complexity.
In order to reduce the performance loss of UMP BP-based decoding algorithm relative to LLR-BP decoding algorithm,an improved UMP BP-based decoding algorithm is proposed.When the check nodes process the message,the normalized BP-based decoding algorithm and offset BP-based decoding algorithm are integrated effectively by setting a correction factor and an offset factor reasonably.When the variable nodes process the message,an oscillation compensation algorithm based on LLR-BP decoding algorithm is introduced.Simulation results show that based on the irregular LDPC codes and under the condition of the same bit error rate within a certain range,the improved UMP BP-based decoding algorithm improves the decoding performance greatly compared with the three decoding algorithms which are based on UMP BP,normalized BP and offset BP decoding algorithms,respectively,and therefore quite efficiently approaches to the LLR-BP decoding algorithm which has excellent performance.