In this paper, a performance analysis of multi-antenna spectrum sensing techniques is carried out. Both well known algorithms, such as Energy Detector (ED) and eigenvalue based detectors, and an eigenvector based algorithm, are considered. With the idea of auxiliary noise variance estimation, the performance analysis is extended to the hybrid approaches of the considered detectors. Moreover, optimization for Hybrid ED under constant estimation plus detection time is performed. Performance results are evaluated in terms of Receiver Operating Characteristic (ROC) curves and performance curves, i.e., detection probability as a function of the Signal-to-Noise Ratio (SNR). It is concluded that the eigenvector based detector and its hybrid approach are able to approach the optimal Neyman-Pearson performance.

Performance Analysis of Multi-Antenna Hybrid Detectors and Optimization with Noise Variance Estimation / Riviello, DANIEL GAETANO; Dhakal, Pawan; Garello, Roberto. - ELETTRONICO. - (2015), pp. 14-19. (Intervento presentato al convegno COCORA 2015, The Fifth International Conference on Advances in Cognitive Radio tenutosi a Barcelona, Spain nel 19-24 Aprile 2015).

Performance Analysis of Multi-Antenna Hybrid Detectors and Optimization with Noise Variance Estimation

RIVIELLO, DANIEL GAETANO;DHAKAL, PAWAN;GARELLO, Roberto
2015

Abstract

In this paper, a performance analysis of multi-antenna spectrum sensing techniques is carried out. Both well known algorithms, such as Energy Detector (ED) and eigenvalue based detectors, and an eigenvector based algorithm, are considered. With the idea of auxiliary noise variance estimation, the performance analysis is extended to the hybrid approaches of the considered detectors. Moreover, optimization for Hybrid ED under constant estimation plus detection time is performed. Performance results are evaluated in terms of Receiver Operating Characteristic (ROC) curves and performance curves, i.e., detection probability as a function of the Signal-to-Noise Ratio (SNR). It is concluded that the eigenvector based detector and its hybrid approach are able to approach the optimal Neyman-Pearson performance.
2015
978-1-61208-403-9
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2615584
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