A Channel Attention-Based Denoising Autoencoder U-Net and Classifier (UNA-DAEC) for Signal Identification Under Challenging SNR Conditions

A Channel Attention-Based Denoising Autoencoder U-Net and Classifier (UNA-DAEC) for Signal Identification Under Challenging SNR Conditions

The use of Low-Power Wide Area Network (LPWAN) technologies, such as Long Range (LoRa), Sigfox, and IEEE 802.15.4g (ZigBee), has grown significantly, addressing a wide range of applications including smart metering, agriculture, smart homes, and healthcare. These technologies are valued for their si...

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Bibliographic Details
Main Authors: Ife Olalekan Ebo, Idowu Ajayi, Lina Mroueh, Youmni Ziade, Sylvain Azarian
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Autoencoder
channel attention
convolutional neural network
deep learning
denoising auto-encoder
low-power wireless area network
Online Access:https://ieeexplore.ieee.org/document/10980283/
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