DIR-Net: Deep Residual Polar Decoding Network Based on Information Refinement

Polar codes are closer to the Shannon limit with lower complexity in coding and decoding. As traditional decoding techniques suffer from high latency and low throughput, with the development of deep learning technology, some deep learning-based decoding methods have been proposed to solve these prob...

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Bibliographic Details
Published in:	Entropy (Basel, Switzerland) Vol. 24; no. 12; p. 1809
Main Authors:	Song, Bixue, Feng, Yongxin, Wang, Yang
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 12.12.2022 MDPI
Subjects:	Algorithms Artificial neural networks attention mechanism Bit error rate Channels Codes Communication Computational linguistics Computer simulation Decoding decoding subnetwork Deep learning denoising subnetwork DIR-Net Error correction & detection Evaluation Fading channels Information retrieval Language processing Machine learning Methods Natural language interfaces Neural networks polar codes denoising subnetwork deep learning polar codes decoding subnetwork attention mechanism DIR-Net
ISSN:	1099-4300, 1099-4300
Online Access:	Get full text
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