A Cognitive Radio Spectrum Sensing Method for an OFDM Signal Based on Deep Learning and Cycle Spectrum
Joint Authors
Pan, Guangliang
Li, Jun
Lin, Fei
Source
International Journal of Digital Multimedia Broadcasting
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-06
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Telecommunications Engineering
Electronic engineering
Information Technology and Computer Science
Abstract EN
In a cognitive radio network (CRN), spectrum sensing is an important prerequisite for improving the utilization of spectrum resources.
In this paper, we propose a novel spectrum sensing method based on deep learning and cycle spectrum, which applies the advantage of the convolutional neural network (CNN) in an image to the spectrum sensing of an orthogonal frequency division multiplex (OFDM) signal.
Firstly, we analyze the cyclic autocorrelation of an OFDM signal and the cyclic spectrum obtained by the time domain smoothing fast Fourier transformation (FFT) accumulation algorithm (FAM), and the cyclic spectrum is normalized to gray scale processing to form a cyclic autocorrelation gray scale image.
Then, we learn the deep features of layer-by-layer extraction by the improved CNN classic LeNet-5 model.
Finally, we input the test set to verify the trained CNN model.
Simulation experiments show that this method can complete the spectrum sensing task by taking advantage of the cycle spectrum, which has better spectrum sensing performance for OFDM signals under a low signal-noise ratio (SNR) than traditional methods.
American Psychological Association (APA)
Pan, Guangliang& Li, Jun& Lin, Fei. 2020. A Cognitive Radio Spectrum Sensing Method for an OFDM Signal Based on Deep Learning and Cycle Spectrum. International Journal of Digital Multimedia Broadcasting،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1169996
Modern Language Association (MLA)
Pan, Guangliang…[et al.]. A Cognitive Radio Spectrum Sensing Method for an OFDM Signal Based on Deep Learning and Cycle Spectrum. International Journal of Digital Multimedia Broadcasting No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1169996
American Medical Association (AMA)
Pan, Guangliang& Li, Jun& Lin, Fei. A Cognitive Radio Spectrum Sensing Method for an OFDM Signal Based on Deep Learning and Cycle Spectrum. International Journal of Digital Multimedia Broadcasting. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1169996
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169996