Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT
The development of spectral efficient solutions for internet of things (IoT) face challenges primarily due to the large-scale placement of an immense number of sensors and devices. Cognitive radio (CR) technology is considered as a potential solution to resolve the spectrum scarcity problems of IoT....
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9638681/ |
| _version_ | 1818969108484456448 |
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| author | Zeba Idrees Muhammad Usman Hasan Erteza Gelani Lirong Zheng |
| author_facet | Zeba Idrees Muhammad Usman Hasan Erteza Gelani Lirong Zheng |
| author_sort | Zeba Idrees |
| collection | DOAJ |
| description | The development of spectral efficient solutions for internet of things (IoT) face challenges primarily due to the large-scale placement of an immense number of sensors and devices. Cognitive radio (CR) technology is considered as a potential solution to resolve the spectrum scarcity problems of IoT. Incorporation of CR in IoT encounters various challenges including fast response and efficient spectrum sensing even in low signal to noise ratio. In this study we integrate the basic functionalities of the both CR and IoT technology and present a five layered framework for CR enabled IoT. In addition to the framework we also proposed and develop a spectrum sensing algorithm for CR-based IoT architecture, meeting the efficiency and time sensitivity requirements. The proposed algorithm is more accurate, robust to noisy environment and four times faster than existing approaches. The developed algorithm is compared with existing blind spectrum sensing techniques in term of detection performance, optimization methods and computational complexity. Experimental evaluations with real wireless microphone signals demonstrate the effectiveness of the proposed scheme and show superiority over existing ones. |
| first_indexed | 2024-12-20T14:15:21Z |
| format | Article |
| id | doaj.art-61eba91a713a43cea8cea7985a992eee |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-20T14:15:21Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-61eba91a713a43cea8cea7985a992eee2022-12-21T19:38:03ZengIEEEIEEE Access2169-35362021-01-01916599616600710.1109/ACCESS.2021.31333369638681Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoTZeba Idrees0https://orcid.org/0000-0002-7918-0440Muhammad Usman1Hasan Erteza Gelani2https://orcid.org/0000-0002-3307-5899Lirong Zheng3https://orcid.org/0000-0001-9588-0239School of Information Science and Engineering, Fudan University, Shanghai, ChinaSchool of Environmental Science and Engineering, Fudan University, Shanghai, ChinaElectrical Engineering Department, University of Engineering and Technology Lahore, Lahore, PakistanSchool of Information Science and Engineering, Fudan University, Shanghai, ChinaThe development of spectral efficient solutions for internet of things (IoT) face challenges primarily due to the large-scale placement of an immense number of sensors and devices. Cognitive radio (CR) technology is considered as a potential solution to resolve the spectrum scarcity problems of IoT. Incorporation of CR in IoT encounters various challenges including fast response and efficient spectrum sensing even in low signal to noise ratio. In this study we integrate the basic functionalities of the both CR and IoT technology and present a five layered framework for CR enabled IoT. In addition to the framework we also proposed and develop a spectrum sensing algorithm for CR-based IoT architecture, meeting the efficiency and time sensitivity requirements. The proposed algorithm is more accurate, robust to noisy environment and four times faster than existing approaches. The developed algorithm is compared with existing blind spectrum sensing techniques in term of detection performance, optimization methods and computational complexity. Experimental evaluations with real wireless microphone signals demonstrate the effectiveness of the proposed scheme and show superiority over existing ones.https://ieeexplore.ieee.org/document/9638681/Cognitive radiosInternet of Thingsprinciple component analysisspectrum sensing |
| spellingShingle | Zeba Idrees Muhammad Usman Hasan Erteza Gelani Lirong Zheng Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT IEEE Access Cognitive radios Internet of Things principle component analysis spectrum sensing |
| title | Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT |
| title_full | Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT |
| title_fullStr | Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT |
| title_full_unstemmed | Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT |
| title_short | Fast and Robust Spectrum Sensing for Cognitive Radio Enabled IoT |
| title_sort | fast and robust spectrum sensing for cognitive radio enabled iot |
| topic | Cognitive radios Internet of Things principle component analysis spectrum sensing |
| url | https://ieeexplore.ieee.org/document/9638681/ |
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