Deep Learning-Aided Belief Propagation Decoder for Polar Codes

This paper presents deep learning (DL) methods to optimize polar belief propagation (BP) decoding and concatenated LDPC-polar codes. First, two-dimensional offset Min-Sum (2-D OMS) decoding is proposed to improve the error-correction performance of existing normalized Min-Sum (NMS) decoding. Two opt...

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Bibliographic Details
Published in:	IEEE journal on emerging and selected topics in circuits and systems Vol. 10; no. 2; pp. 189 - 203
Main Authors:	Xu, Weihong, Tan, Xiaosi, Be'ery, Yair, Ueng, Yeong-Luh, Huang, Yongming, You, Xiaohu, Zhang, Chuan
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.06.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms ASIC implementation Back propagation Belief propagation belief propagation (BP) Circuits and systems CMOS Codes Complexity theory concatenated codes Decoders Decoding Deep learning Error correction Hardware Iterative decoding Machine learning Optimization Polar codes Propagation Throughput
ISSN:	2156-3357, 2156-3365
Online Access:	Get full text
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