Spectrum Sensing for Cognitive Radio Networks over fading channels

Due to rapid advancements in wireless communication and broader application of these wireless networks in the world, efficient utilization of the spectrum has been a persuasive issue for researchers. This has enabled the development of an intelligent network that can adapt to varying channel conditions by analyzing available spectrum frequency band and increasing the efficiency of an otherwise underutilized spectrum. This paper focuses on the spectrum sensing function of the Cognitive Radio in order to detect and utilize empty spaces in the spectrum without creating interference to the primary user. In this paper a quantitative analysis of two broader groups of spectrum sensing techniques namely Energy detection and Matched filter detection has been presented. A performance analysis based on the Probability of detection and probability of false alarming at different SNR levels is conducted under different fading channel models i.e. Additive White Guassian Noise (AWGN), flat fading and Rayleigh fading channels. A comparison between the above mentioned spectrum sensing techniques proofs low probability of false alarm, when Matched filter detection is used.