Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems
Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and the power consumption of the hardware circuits....
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2015/654958 |
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| author | Taha A. Khalaf Mohammed Y. Abdelsadek Mohammed Farrag |
| author_facet | Taha A. Khalaf Mohammed Y. Abdelsadek Mohammed Farrag |
| author_sort | Taha A. Khalaf |
| collection | DOAJ |
| description | Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and the power consumption of the hardware circuits. Compressive sensing (CS) is successfully deployed to solve this problem. Although CS solves the higher sampling rate problem, it does not reduce complexity to a large extent. Spectrum sensing via CS technique is performed in three steps: sensing compressed measurements, reconstructing the Nyquist rate signal, and performing spectrum sensing on the reconstructed signal. Compressed detectors perform spectrum sensing from the compressed measurements skipping the reconstruction step which is the most complex step in CS. In this paper, we propose a novel compressed detector using energy detection technique on compressed measurements sensed by the discrete cosine transform (DCT) matrix. The proposed algorithm not only reduces the computational complexity but also provides a better performance than the traditional energy detector and the traditional compressed detector in terms of the receiver operating characteristics. We also derive closed form expressions for the false alarm and detection probabilities. Numerical results show that the analytical expressions coincide with the exact probabilities obtained from simulations. |
| format | Article |
| id | doaj-art-75477717486743b6bef844e04610ee2e |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-75477717486743b6bef844e04610ee2e2025-02-03T05:51:41ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772015-01-01201510.1155/2015/654958654958Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio SystemsTaha A. Khalaf0Mohammed Y. Abdelsadek1Mohammed Farrag2Department of Electrical Engineering, University of Tabuk, Tabuk 71491, Saudi ArabiaDepartment of Electrical Engineering, Assiut University, Assiut 71516, EgyptDepartment of Electrical Engineering, Assiut University, Assiut 71516, EgyptSpectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and the power consumption of the hardware circuits. Compressive sensing (CS) is successfully deployed to solve this problem. Although CS solves the higher sampling rate problem, it does not reduce complexity to a large extent. Spectrum sensing via CS technique is performed in three steps: sensing compressed measurements, reconstructing the Nyquist rate signal, and performing spectrum sensing on the reconstructed signal. Compressed detectors perform spectrum sensing from the compressed measurements skipping the reconstruction step which is the most complex step in CS. In this paper, we propose a novel compressed detector using energy detection technique on compressed measurements sensed by the discrete cosine transform (DCT) matrix. The proposed algorithm not only reduces the computational complexity but also provides a better performance than the traditional energy detector and the traditional compressed detector in terms of the receiver operating characteristics. We also derive closed form expressions for the false alarm and detection probabilities. Numerical results show that the analytical expressions coincide with the exact probabilities obtained from simulations.http://dx.doi.org/10.1155/2015/654958 |
| spellingShingle | Taha A. Khalaf Mohammed Y. Abdelsadek Mohammed Farrag Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems International Journal of Antennas and Propagation |
| title | Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems |
| title_full | Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems |
| title_fullStr | Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems |
| title_full_unstemmed | Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems |
| title_short | Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems |
| title_sort | compressed measurements based spectrum sensing for wideband cognitive radio systems |
| url | http://dx.doi.org/10.1155/2015/654958 |
| work_keys_str_mv | AT tahaakhalaf compressedmeasurementsbasedspectrumsensingforwidebandcognitiveradiosystems AT mohammedyabdelsadek compressedmeasurementsbasedspectrumsensingforwidebandcognitiveradiosystems AT mohammedfarrag compressedmeasurementsbasedspectrumsensingforwidebandcognitiveradiosystems |