Studentized Extreme Eigenvalue Based Double Threshold Spectrum Sensing Under Noise Uncertainty
The eigenvalue based spectrum sensing is a low-cost spectrum sensing method that detects the presence of the licensed user signal in desired frequency. Traditional single-threshold eigenvalue sensing methods, which are widely used in the literature, can exhibit inadequate performance under low SNR a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2020-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/343896 |
| Summary: | The eigenvalue based spectrum sensing is a low-cost spectrum sensing method that detects the presence of the licensed user signal in desired frequency. Traditional single-threshold eigenvalue sensing methods, which are widely used in the literature, can exhibit inadequate performance under low SNR and noise uncertainty. Therefore, in this study an eigenvalue-based spectrum sensing method is proposed using a double threshold with the studentized extreme eigenvalue distribution function. The results that threshold values obtained for the proposed method were simulated in Rayleigh fading channels. The results were compared with traditional methods and they were observed to be more accurate. |
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| ISSN: | 1330-3651 1848-6339 |