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An Improved Path Splitting Decision-Aided SCL Decoding Algorithm for Polar Codes

delete2021-11-01
delete4
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OA
AI
X
Xiumin Wang
H
Hongchao Zhang
J
Jun Li *
X
Xiupin Bao
K
Kunyu Xie
DOI:10.1109/LCOMM.2021.3109795delete
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Abstract

Abstract

En 中文
Although the traditional successive cancellation list (SCL) decoding algorithm can greatly improve the performance of successive cancellation (SC) decoding algorithm, multiple path splitting and sorting operations increase the complexity. In order to reduce the complexity of the SCL algorithm, a new path splitting decision strategy is proposed to reduce the number of path splitting (PSN). This strategy is based on a new auxiliary path metric (APM) proposed in this letter, which is used to identify whether the decoding path is wrong. Wrong paths can be avoided by comparing the predicted APM with the threshold. The simulation results show that the proposed path splitting decision-aided SCL (PSD-SCL) algorithm reduces the complexity compared with other list decoding algorithms with small performance loss at high signal-noise ratio (SNR).
Keywords:
Decoding
Codes
Reliability
Signal to noise ratio
Polar codes
Measurement
Prediction algorithms
Polar codes
successive cancellation list decoding
path splitting decision
path metric

Journal

IEEE Communications Letters cover
IEEE Communications Letters
IF:
4.4
Papers:
1.3W
Citations:
2.2W

Organization

W
Wuxi University
Scholars:
810
Papers: 659
Citations: 42
C
China Jiliang University
Scholars:
9.8K
Papers: 6.3K
Citations: 7.2K