Adaptive Double-Threshold Based Energy and Matched Filter Detector in Cognitive Radio Networks

In this paper we propose a new cooperative spectrum sensing method using adaptive double threshold energy and matched filter detector in cognitive radio networks. The energy detector (ED) performance is highly degraded under noise uncertainty condition. Also, ED cannot well differentiate between the signal and noise, if the detected observational value of the primary user (PU) lies in the confused region i.e., between signal and noise. We propose a scheme based on adaptive double threshold that uses matched filter (MF) detector for the reliable detection in the confused region and energy efficient ED for the clear region where the detector can easily differentiate between signal and noise and makes its own local decision. The fusion center collects the local decisions and observational values of the secondary users and then makes the final decision to ascertain whether the primary user is present or not. Simulation results shows that our proposed method has higher detection performance as compared to other spectrum sensing methods.