Analysis of Different Spectrum Sensing Techniques in Cognitive Radio Network

Cognitive radio permits unlicensed users to access licensed frequency bands through dynamic spectrum access so as to reduce spectrum deficiency. This requires intelligent spectrum sensing techniques like co-operative sensing which creates use of information from number of users. The main challenge in any cognitive radio system is to maximize secondary user’s throughput while limiting interference imposed on licensed users. In this consideration finding the optimal sensing and transmission timing strategies and accurate sensing techniques are of great importance in a cognitive radio network. In this paper, examine different on Matched filtering, Energy detection and Cyclostationary feature detection cognitive radio spectrum sensing techniques over AWGN, Rician fading and Rayleigh fading channel. It also contain combined analysis of Matched filtering, Energy detection and Cyclostationary feature detection technique for common scenario through decision accuracy vs SNR plots over AWGN, Rician fading and Rayleigh fading channel. Keyword–Cognitive Radio (CR), Additive White Gaussian Noise (AWGN), Dynamic Spectrum Allocation (DSA), Primary User (PU), Secondary User (SU).