An Optimized Sensing and Detection of Cognitive Radio Network using Monte Carlo Simulation
نویسندگان
چکیده
The Cognitive Radio Network is intelligent network, which has the capability to efficiently utilize the available spectrum using various spectrum-sensing techniques, in addition with the intelligent energy consumption and bandwidth allocation. In this paper we are simulating the cognitive radio network using Monte-Carlo simulation model. The proposed system is tested under Additive White Gaussian noise (AWGN) channel and Rayleigh Fading Channel environment. During simulation the probability of detection (Pd) is calculated for given signal to noise ratio (SNR) and false alarm rate (Pf). To enhance the system performance median filter is implemented which significantly enhances the performance of detection probability for given SNR and Pf.
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