International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 162 - Number 4 |
Year of Publication: 2017 |
Authors: Abhinav Shukla, Puran Gour |
10.5120/ijca2017913258 |
Abhinav Shukla, Puran Gour . An Optimized Sensing and Detection of Cognitive Radio Network using Monte Carlo Simulation. International Journal of Computer Applications. 162, 4 ( Mar 2017), 7-11. DOI=10.5120/ijca2017913258
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.