Kadjo, J.-M.; Yao, K.C.; Mansour, A.; Le Jeune, D. Noncooperative Spectrum Sensing Strategy Based on Recurrence Quantification Analysis in the Context of the Cognitive Radio. Signals2024, 5, 438-459.
Kadjo, J.-M.; Yao, K.C.; Mansour, A.; Le Jeune, D. Noncooperative Spectrum Sensing Strategy Based on Recurrence Quantification Analysis in the Context of the Cognitive Radio. Signals 2024, 5, 438-459.
Kadjo, J.-M.; Yao, K.C.; Mansour, A.; Le Jeune, D. Noncooperative Spectrum Sensing Strategy Based on Recurrence Quantification Analysis in the Context of the Cognitive Radio. Signals2024, 5, 438-459.
Kadjo, J.-M.; Yao, K.C.; Mansour, A.; Le Jeune, D. Noncooperative Spectrum Sensing Strategy Based on Recurrence Quantification Analysis in the Context of the Cognitive Radio. Signals 2024, 5, 438-459.
Abstract
This paper addresses the problem of non-cooperative spectrum sensing in very low signal noise ratio (SNR) conditions. In our approach, detecting an unoccupied bandwidth consists to detect the presence or absence of a communication signal on this bandwidth. Major well known communication signals may contain hidden periodicities, we use the Recurrence Quantification Analysis (RQA) to reveal the hidden periodicities. RQA is very sensitive to a reliable estimation of the phase space dimension m or the time delay τ. In view of the limitations of algorithms proposed in the literature, we have proposed a new algorithm to estimate simultaneously the optimal values of m and τ. The new proposed optimal values allow the states reconstruction of the observed signal and then the estimation of the distance matrix. This distance matrix has particular properties which we have exploited to propose the Recurrence Analysis based Detector (RAD). RAD can detect a communication signal in a very low SNR condition. Using Receiver Operating Characteristic curves, our experimental results corroborate the robustness of our proposed algorithm comparing to classical widely used algorithms.
Computer Science and Mathematics, Signal Processing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
