.png){kind=icon}
Return
Large Scale LP Decoding with Low Complexity
.png){kind=icon}
PRE
AI
DOI：10.1109/LCOMM.2013.101413.130826.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Linear program (LP) decoding has become increasingly popular for error-correcting codes due to its simplicity and promising performance. Low-complexity and efficient iterative algorithms for LP decoding are of great importance for practical applications. In this paper we focus on solving the binary LP decoding problem by using the alternating direction method of multipliers (ADMM). Our main contribution is that we propose a linear-complexity algorithm for the projection onto a parity polytope (having a computational complexity of O(d), where d is the check-node degree), as compared to recent work [1], which has a computational complexity of O(d log d). In particular, we show that the projection onto the parity polytope can be transformed to a projection onto a simplex.
Keywords:
Distributed optimization
LP decoding
alternating direction method of multipliers
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.4
Papers:
1.3W
Citations:
2.2W
Organization
Cited Papers
ShareSave
Analysis and Design of High-Efficiency Bidirectional GaN-Based CLLC Resonant Converter.png)
Energies
OAAI
EnergiesIF0
OAAIShareSaveShareSave no more
no more