PERFORMANCE COMPARISION OF ENERGY DETECTOR USING VARIOUS ALGORITHMS FOR COGNITIVE RADIO NETWORKS

Abstract

Spectrum sensing is very important technique in cognitive radio network. Selection of appropriate threshold for spectrum sensing defines the performance of the cognitive radio. Conventional method of threshold selection suffers from the signal and noise fluctuations. So more flexible spectrum sensing algorithms are used which adapt to changing signal and noise power. This work focusses on energy detection based spectrum sensing algorithm as it is simple and does not require prior information. Collision between cognitive users and the primary users determine the detection performance. Performance of adaptive spectrum sensing algorithm and adaptive double threshold algorithm are compared with the conventional double threshold algorithm for the AWGN channel, Rayleigh and Nakagami fading channels. Theoretical analysis and simulation result showed that interference level to primary users is reduced and detection performance is significantly improved using adaptive double threshold algorithm.