Spectrum sensing based on capon power spectral density estimation
Date
2015-04-01
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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.
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Keywords
Spectrum holes, Cognitive radio, Spectrum sensing