WDLReconNet: Compressive Sensing Reconstruction With Deep Learning Over Wireless Fading Channels

WDLReconNet: Compressive Sensing Reconstruction With Deep Learning Over Wireless Fading Channels

Deep learning has been exploited in compressive sensing to reduce the computational complexity of reconstruction algorithms. However, existing deep-learning-based reconstruction algorithms might result in poor performance, when applied in wireless transmission environments. First, the impact of chan...

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Bibliographic Details
Main Authors: Hancheng Lu, Lei Bo
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Compressive sensing (CS)
deep learning
reconstruction algorithms
wireless fading channels
convolutional neural network (CNN)
Online Access:https://ieeexplore.ieee.org/document/8648366/

Internet

https://ieeexplore.ieee.org/document/8648366/

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