Deep non-cooperative spectrum sensing over Rayleigh fading channel

Deep non-cooperative spectrum sensing over Rayleigh fading channel

In this paper, we propose a robust non-cooperative spectrum sensing algorithm based on deep learning over Rayleigh fading channel. We conduct noise cancellation on the received sensing data using the stacked convolutional auto-encoder (SCAE) as a pre-processing step. The series of the denoised signa...

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Bibliographic Details
Main Authors: Su, Zhengyang, Teh, Kah Chan, Razul, Sirajudeen Gulam, Kot, Alex Chichung
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2022
Subjects:
Engineering::Electrical and electronic engineering
Deep Learning
Spectrum Sensing
Online Access:https://hdl.handle.net/10356/163818
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Institution: Nanyang Technological University
Language: English
Description
Summary:In this paper, we propose a robust non-cooperative spectrum sensing algorithm based on deep learning over Rayleigh fading channel. We conduct noise cancellation on the received sensing data using the stacked convolutional auto-encoder (SCAE) as a pre-processing step. The series of the denoised signal in the time domain is then fed into the proposed Hybrid CNN-SA-GRU (H-CSG) network. The proposed network combines convolutional neural network (CNN), self-attention (SA) modules and gate recurrent unit (GRU). It can extract input features from spatial and temporal domains. The proposed algorithm has been shown to be effective and robust in detecting weak signals at the low signal-to-noise ratio (SNR) level.

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