Spectrum sensing based on capon power spectral density estimation

Abstract

Cognitive radio (CR) technology has evolved to solve the spectrum scarcity problem and improve spectrum utilization. Spectrum sensing is a CR function that allows secondary users to efficiently utilize the spectrum without interfering with primary users. The performance of this function depends on the efficiency of the used detection method. In this thesis, we propose a spectrum sensing based on the Capon Power Spectral Density (PSD) estimation method. The proposed method estimates the received PSD, and uses it to identify free and busy channels. A cooperative spectrum sensing approach is also introduced. The goal is to solve the common hidden node problem and help devices without CR capability to identify free channels. Experimental results show that the proposed method outperforms the spectrum sensing based on the Periodogram method in detecting both busy and free channels. In addition, simulation results show that the cooperative approach improves the spectrum sensing function.