Time domain averaging and correlation-based improved spectrum sensing method for cognitive radio
Based on the combination of time domain averaging and correlation, we propose an effective time domain averaging and correlation-based spectrum sensing (TDA-C-SS) method used in very low signal-to-noise ratio (SNR) environments. With the assumption that the received signals from the primary users ar...
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Main Authors: | , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2014
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/103909 http://hdl.handle.net/10220/20038 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Based on the combination of time domain averaging and correlation, we propose an effective time domain averaging and correlation-based spectrum sensing (TDA-C-SS) method used in very low signal-to-noise ratio (SNR) environments. With the assumption that the received signals from the primary users are deterministic, the proposed TDA-C-SS method processes the received samples by a time averaging operation to improve the SNR. Correlation operation is then performed with a correlation matrix to determine the existence of the primary signal in the received samples. The TDA-C-SS method does not need any prior information on the received samples and the associated noise power to achieve improved sensing performance. Simulation results are presented to show the effectiveness of the proposed TDA-C-SS method. |
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