Bidirectional Deep Learning Decoder for Polar Codes in Flat Fading Channels

One of the main issues facing in the future wireless communications is ultra-reliable and low-latency communication. Polar codes are well-suited for such applications, and recent advancements in deep learning have shown promising results in enhancing polar code decoding performance. We propose a rob...

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Bibliographic Details
Published in:	IEEE access Vol. 12; pp. 149580 - 149592
Main Authors:	Aziz, Md Abdul, Rahman, Md Habibur, Abrar Shakil Sejan, Mohammad, Tabassum, Rana, Hwang, Duck-Dong, Song, Hyoung-Kyu
Format:	Journal Article
Language:	English
Published:	IEEE 2024
Subjects:	Accuracy bi-directional long-short-term memory (Bi-LSTM) Binary phase shift keying convolutional neural network (CNN) Decoding deep learning (DL) deep neural network (DNN) Encoding Fading channels Iterative decoding Long short term memory PER Polar code Polar codes Reliability signal-to-noise ratio (SNR) successive cancellation (SC) Turbo codes wireless communication
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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