Design and analysis of spectrum sensing in cognitive radio based on energy detection

Cognitive Radio is an intelligent radio designed to automatically detect the best wireless channel in wireless spectrum that is unused at a specific time. It is software defined radio in which the operating parameters such as modulation type, power or spectrum band change by software. Spectrum sensing is one of the most important functions of cognitive radio. It is used to detect the activity of the licensed users in a selected band. This paper used the Energy detection method for spectrum sensing to sense the presence of primary users. The energy detection algorithm is coded in MATLAB to determine the availability of used spectrum of licensed band. Probability of detection is calculated as the ratio between the number of times the signal passes the threshold value and the total number of trails using Monte-Carlo method. Three different modulation techniques BPSK, QPSK and QAM under Additive White Gaussian Noise (AWGN) are specified for increasing signal quality and detection. In this work PD of primary user at lower signal to noise ratio up to −10dB with fixed Probability of false alarm at 0.00001, 0.0001, 0.001 and 0.01 is analyzed. After analysis it is observed that PD increases with increase in PFA. It is also observed that among these modulation techniques, QAM is the best method for the spectrum sensing.