Node-Wise Scheduling Algorithm of ADMM Decoding Based on Line Segment Projection

In order to simplify the node-wise scheduling algorithm of the alternating direction method of multipliers (NS-ADMM) decoding, approximate line segment projection algorithm (LSA) is adopted to perform the projection in the node-wise scheduling algorithm. Experimental results show that using approxim...

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Bibliographic Details
Published in:IEEE communications letters Vol. 26; no. 4; pp. 738 - 742
Main Authors: Xia, Qiaoqiao, He, Pinquan, Wang, Xin, Liu, Huiyang, Zhang, Qinglin
Format: Journal Article
Language:English
Published: New York IEEE 01.04.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Alternating direction method of multipliers (ADMM)
Approximation algorithms
check polytope projection
Convergence
Decoding
Dynamic scheduling
Error correction
low-density parity-check (LDPC) codes
Message passing
message scheduling
Nodes
Projection
Projection algorithms
Schedules
Scheduling
Scheduling algorithms
Segments
ISSN:1089-7798, 1558-2558
Online Access:Get full text
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Summary:In order to simplify the node-wise scheduling algorithm of the alternating direction method of multipliers (NS-ADMM) decoding, approximate line segment projection algorithm (LSA) is adopted to perform the projection in the node-wise scheduling algorithm. Experimental results show that using approximate line segment projection instead of precise projection in node-wise scheduling algorithm will yield a poor frame error rate (FER) performance. To solve this problem, dynamic scheduling strategy that selects the message-passing schedule according to the convergence status of the check node is proposed. Simulation results demonstrate that the modified node-wise scheduling algorithm based on line segment projection outperforms existing decoding algorithms in terms of FER performance and convergence speed, while it has good error correction performance with a lower computational complexity.
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2022.3143235