Compressive Spectrum Sensing in Cognitive Radio Networks Using Machine Learning |
Author(s): |
| Sunil khoja , Sagar Institute of Science and Technology, Bhopal ; Anoop Tiwari, SISTEC |
Keywords: |
| Compressed Sensing, Cognitive Radio, Wireless Communication |
Abstract |
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The increasing demand of wireless communication systems aims to overcome the problem of limited radio frequency spectrum by helping to achieve improved spectral management, utilization, and efficiency. For wireless communication networks, cognitive radio (CR) can be used to obtain the available spectrum. Using compressive sensing (CS), sampling and compression of the spectrum signal can be simultaneously achieved, and the original signal can be accurately recovered from the sampling data. We propose deep signal recovery algorithm for recovering data in the context of CS (Compressed sensing). In this work, deep learning compressive sensing and reconstruction technique to achieve better efficiency. |
Other Details |
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Paper ID: IJSRDV10I40027 Published in: Volume : 10, Issue : 4 Publication Date: 01/07/2022 Page(s): 111-115 |
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