Spectrum energy detection in cognitive radio networks based on a novel adaptive threshold energy detection method

Abstract Cognitive radio (CR) is a smart communication innovation in the development of the network. With advances in remote communications, the issue of bandwidth has proven to be more unique. The innovation of cognitive radio has turned as an approach to take care of this problem by enabling the unlicensed clients to utilize the authorized bands. A constrained available spectrum has been put in the way of impediments by the surpassing interest of remote presentations. To locate the unused spectrum in CR need one of the fundamental technique based on spectrum energy detection. The fundamental prerequisite for enabling CRs has been using the authorized spectrum for the auxiliary premise is not making impedance Primary Users (PU). Spectrum detection allows intelligent users to distinguish between unrecognized parts of the radio spectrum self-determination, and exempt the primary users from interrupting this way. Energy detection based spectrum detecting has been proposed for this work based on the Adaptive Threshold Spectrum Energy Detection (ATSED) strategy. By using ATSED the spectral detection performance can be significantly improved when the noise is uncertain and the primary user can reject the interference level. In this work, a framework model is developed based on spectrum energy detection using Matlab Simulink software. The simulation results demonstrate that the probability of detection is increased fundamentally when Signal to Noise Ratio (SNR) increases. It is likewise watched that the detection of probability decreases when the bandwidth factor increases.