A novel spectrum sensing algorithm based on support vector machine is proposed. The idea is to map the received signals into a multi-dimensional feature space obtained from well-known spectrum sensing statistics and their higher-order combinations. The approach has been implemented and validated on a software-defined radio testbed. Experimental results have shown the receiver operating characteristic (ROC) curve of the proposed detector can outperform classical spectrum sensing approaches without requiring knowledge of the noise variance.
Spectrum sensing by higher-order SVM-based detection / Coluccia, A.; Fascista, A.; Ricci, G.. - 2019:(2019), pp. 1-5. (Intervento presentato al convegno 27th European Signal Processing Conference, EUSIPCO 2019 tenutosi a A Coruna Conference Center, PALEXCO, esp) [10.23919/EUSIPCO.2019.8903028].
Spectrum sensing by higher-order SVM-based detection
Fascista A.;
2019-01-01
Abstract
A novel spectrum sensing algorithm based on support vector machine is proposed. The idea is to map the received signals into a multi-dimensional feature space obtained from well-known spectrum sensing statistics and their higher-order combinations. The approach has been implemented and validated on a software-defined radio testbed. Experimental results have shown the receiver operating characteristic (ROC) curve of the proposed detector can outperform classical spectrum sensing approaches without requiring knowledge of the noise variance.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
