Spectrum Sensing for Cognitive Radio using Deep Autoencoder Neural Network and SVM
Agus Subekti, Hilman Ferdinandus Pardede, Rika Sustika, Suyoto Suyoto · 2018
Cognitive radio is one of solution to increase the efficient usage of frequency by spectrum sharing. One important compenent in the spectrum sharing is spectrum management system. The spectrum management system distributes information of white space. The system collects the information by performing spectrum monitoring. Spectrum monitoring is peformed by spectrum sensing. Spectrum sensing is challanging in multi radio environment because it has to discriminate several different radio system. In this paper, we proposed a spectrum sensing method based on deep auto encoder neural network and suport vector machine (SVM). Auto encoder neural network is used for automatic feature learning. The output of the feature learning then will be classified using support vector machine (SVM). SVM will classify input signal as primary user or secondary user. Using the proposed method, the sensing accuracy achieve the good performance up to 95 %.