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

Security and Communication Networks

Novel Early Termination Method of an ADMM-Penalized Decoder for LDPC Codes in the IoT

Biao Wang

Published Oct 14, 2022• 0 citations
Publisher

Abstract

As a critical communication technology, low-density parity-check (LDPC) codes are widely concerned with the Internet of things (IoT). To increase the convergence rate of the alternating direction method of multiplier (ADMM)-penalized decoder for LDPC codes, a novel early termination (ET) method is presented by computing the average sum of the hard decision (ASHD) during each ADMM iteration. In terms of the flooding scheduling and layered scheduling ADMM-penalized decoders, the simulation results show that the proposed ET method can significantly reduce the average number of iterations at low signal-to-noise ratios (SNRs) with negligible decoding performance loss.

DOI
10.1155/2022/4599105

Related papers

Efficient Early Termination Criterion for ADMM Penalized LDPC Decoder

Biao Wang, Xiaopeng Jiao, Jianjun Mu +1 more

By tracking the changing rate of hard decisions during every two consecutive iterations of the alternating direction method of multipliers (ADMM) penalized decoding, an efficient early termination (ET) criterion is proposed to improve the convergence rate of ADMM penalized decoder for low-density parity-check (LDPC) codes. Compared to the existing ET criterion for ADMM penalized decoding, the proposed method can reduce the average number of iterations significantly at low signal-to-noise ratios with negligible performance degradation.

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences•Jan 1, 2018•2 citations

Early Termination Criterion of ADMM-LP Decoder for LDPC Codes

Ruirui XUE, Biao Wang, Zhongfei Wang

In order to terminate iterations earlier of the linear programming (LP) decoder based on the alternating direction method of multipliers (ADMM) (ADMM-LP), this letter proposes an early termination (ET) criterion based on the number of parity-check constraints of iterative solution vector. The criterion can be used to detect erroneous codewords in advance and thereby avoid unnecessary iterations, without increasing the additional computational complexity. Compared with existing termination criteria of ADMM-LP decoding algorithm, the proposed ET criterion can significantly reduce the average number of iterations at low signal-to-noise ratio (SNR) regions with little effect on the decoding performance.

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences•Oct 23, 2025•0 citations

Fast Converging ADMM Penalized Decoding Method Based on Improved Penalty Function for LDPC Codes

Biao Wang

For low-density parity-check (LDPC) codes, the penalized decoding method based on the alternating direction method of multipliers (ADMM) can improve the decoding performance at low signal-to-noise ratios and also has low decoding complexity. There are three effective methods that could increase the ADMM penalized decoding speed, which are reducing the number of Euclidean projections in ADMM penalized decoding, designing an effective penalty function and selecting an appropriate layered scheduling strategy for message transmission. In order to further increase the ADMM penalized decoding speed, through reducing the number of Euclidean projections and using the vertical layered scheduling strategy, this paper designs a fast converging ADMM penalized decoding method based on the improved penalty function. Simulation results show that the proposed method not only improves the decoding performance but also reduces the average number of iterations and the average decoding time.

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences•May 7, 2020•2 citations

Improved ADMM Penalized Decoder for Irregular Low-Density Parity-Check Codes

Xiaopeng Jiao, Haoyuan Wei, Jianjun Mu +1 more

Based on linear programming (LP) decoding with alternating direction method of multipliers (ADMM), Liu et al. proposed an ADMM penalized decoder for low-density parity-check (LDPC) codes that can improve the error rate performance at low signal-to-noise ratios. In this letter, we propose a new ADMM penalized decoder to improve the error rate performance further for irregular LDPC codes. The proposed decoder modifies the penalty term of the objective function by assigning different penalty parameters for different variable node degrees. Simulations over three irregular LDPC codes show that the proposed decoder performs considerably better than the ADMM penalized decoder.

IEEE Communications Letters•Apr 10, 2015•50 citations

Improved approximate check polytope projection algorithm of ADMM penalized decoding for LDPC codes in IoTs

Yue Zhao, Biao Wang

The alternating direction method of multipliers (ADMM) penalized decoding method is a popular technology for low-density parity-check (LDPC) codes in Internet of Things (IoT) communications. In this method, Euclidean projection is a key factor affecting computational complexity. Existing projection algorithms require either sorting operation or iterative execution, resulting in greater computational complexity. By binarizing the indicator vector, this paper proposes an improved approximate check polytope projection algorithm (I-APPA) to improve projection efficiency. The simulation results indicate that I-APPA can reduce calculation steps and improve projection efficiency. Therefore, the proposed I-APPA algorithm is convenient for hardware implementation in IoT devices.

Scientific Reports•Apr 17, 2025•1 citation

Low-Density Parity-Check Decoding Algorithm Based on Symmetric Alternating Direction Method of Multipliers

Ji Zhang, Anmin Chen, Ying Zhang +3 more

The Alternating Direction Method of Multipliers (ADMM) has proven to be an efficient approach for implementing linear programming (LP) decoding of low-density parity-check (LDPC) codes. By introducing penalty terms into the LP decoding model's objective function, ADMM-based variable node penalized decoding effectively mitigates non-integral solutions, thereby improving frame error rate (FER) performance, especially in the low signal-to-noise ratio (SNR) region. In this paper, we leverage the ADMM framework to derive explicit iterative steps for solving the LP decoding problem for LDPC codes with penalty functions. To further enhance decoding efficiency and accuracy, We propose an LDPC code decoding algorithm based on the symmetric ADMM (S-ADMM). We also establish some contraction properties satisfied by the iterative sequence of the algorithm. Through simulation experiments, we evaluate the proposed S-ADMM decoder using three standard LDPC codes and three representative fifth-generation (5G) codes. The results show that the S-ADMM decoder consistently outperforms conventional ADMM penalized decoders, offering significant improvements in decoding performance.

Entropy•Apr 9, 2025•1 citation
As a critical communication technology, low-density parity-check (LDPC) codes are widely concerned with the Internet of things (IoT). To increase the convergence rate of the alternating direction method of multiplier (ADMM)-penalized decoder for LDPC codes, a novel early termination (ET) method is presented by computing the average sum of the hard decision (ASHD) during each ADMM iteration. In terms of the flooding scheduling and layered scheduling ADMM-penalized decoders, the simulation results show that the proposed ET method can significantly reduce the average number of iterations at low signal-to-noise ratios (SNRs) with negligible decoding performance loss.
By tracking the changing rate of hard decisions during every two consecutive iterations of the alternating direction method of multipliers (ADMM) penalized decoding, an efficient early termination (ET) criterion is proposed to improve the convergence rate of ADMM penalized decoder for low-density parity-check (LDPC) codes. Compared to the existing ET criterion for ADMM penalized decoding, the proposed method can reduce the average number of iterations significantly at low signal-to-noise ratios with negligible performance degradation.
In order to terminate iterations earlier of the linear programming (LP) decoder based on the alternating direction method of multipliers (ADMM) (ADMM-LP), this letter proposes an early termination (ET) criterion based on the number of parity-check constraints of iterative solution vector. The criterion can be used to detect erroneous codewords in advance and thereby avoid unnecessary iterations, without increasing the additional computational complexity. Compared with existing termination criteria of ADMM-LP decoding algorithm, the proposed ET criterion can significantly reduce the average number of iterations at low signal-to-noise ratio (SNR) regions with little effect on the decoding performance.
For low-density parity-check (LDPC) codes, the penalized decoding method based on the alternating direction method of multipliers (ADMM) can improve the decoding performance at low signal-to-noise ratios and also has low decoding complexity. There are three effective methods that could increase the ADMM penalized decoding speed, which are reducing the number of Euclidean projections in ADMM penalized decoding, designing an effective penalty function and selecting an appropriate layered scheduling strategy for message transmission. In order to further increase the ADMM penalized decoding speed, through reducing the number of Euclidean projections and using the vertical layered scheduling strategy, this paper designs a fast converging ADMM penalized decoding method based on the improved penalty function. Simulation results show that the proposed method not only improves the decoding performance but also reduces the average number of iterations and the average decoding time.
Based on linear programming (LP) decoding with alternating direction method of multipliers (ADMM), Liu et al. proposed an ADMM penalized decoder for low-density parity-check (LDPC) codes that can improve the error rate performance at low signal-to-noise ratios. In this letter, we propose a new ADMM penalized decoder to improve the error rate performance further for irregular LDPC codes. The proposed decoder modifies the penalty term of the objective function by assigning different penalty parameters for different variable node degrees. Simulations over three irregular LDPC codes show that the proposed decoder performs considerably better than the ADMM penalized decoder.
The alternating direction method of multipliers (ADMM) penalized decoding method is a popular technology for low-density parity-check (LDPC) codes in Internet of Things (IoT) communications. In this method, Euclidean projection is a key factor affecting computational complexity. Existing projection algorithms require either sorting operation or iterative execution, resulting in greater computational complexity. By binarizing the indicator vector, this paper proposes an improved approximate check polytope projection algorithm (I-APPA) to improve projection efficiency. The simulation results indicate that I-APPA can reduce calculation steps and improve projection efficiency. Therefore, the proposed I-APPA algorithm is convenient for hardware implementation in IoT devices.
The Alternating Direction Method of Multipliers (ADMM) has proven to be an efficient approach for implementing linear programming (LP) decoding of low-density parity-check (LDPC) codes. By introducing penalty terms into the LP decoding model's objective function, ADMM-based variable node penalized decoding effectively mitigates non-integral solutions, thereby improving frame error rate (FER) performance, especially in the low signal-to-noise ratio (SNR) region. In this paper, we leverage the ADMM framework to derive explicit iterative steps for solving the LP decoding problem for LDPC codes with penalty functions. To further enhance decoding efficiency and accuracy, We propose an LDPC code decoding algorithm based on the symmetric ADMM (S-ADMM). We also establish some contraction properties satisfied by the iterative sequence of the algorithm. Through simulation experiments, we evaluate the proposed S-ADMM decoder using three standard LDPC codes and three representative fifth-generation (5G) codes. The results show that the S-ADMM decoder consistently outperforms conventional ADMM penalized decoders, offering significant improvements in decoding performance.