Sequential spectrum sensing approach based on suprathreshold stochastic resonance in cognitive radio

The rapid growth in wireless communications has contributed to a huge demand on the deployment of new wireless services in both the licensed and unlicensed frequency spectrum. In fixed spectrum assignments there are many frequencies that are not being properly used. So Cognitive radio is a technology that supports a secondary and opportunistic access to licensed spectrum shows great potential to dramatically improve spectrum utilization. Spectrum sensing performed by secondary users to detect unoccupied spectrum bands is a key enabling technique for cognitive radio. However, the sensing time could be still unacceptably long due to the weak PU signal, particularly in non-Gaussian noise. The goal of this project is to improve the spectrum sensing efficiency, by means of sequential sensing scheme based on Suprathreshold Stochastic Resonance (SSR). The performance metrics such as false alarm rate, detection probability, average sample number (ASN) has been considered for analysis. The technique has been analyzed using MATLAB R2010a simulation tool.