Optimization of spectrum sensing for cognitive sensor network using differential evolution approach in smart environment

The spectrum congestion due to the static spectrum allocation scheme in wireless communication had been an issue for decade. Despite the rapid growth of wireless communications, the emerging of Internet of Things to transform everyday objects into smart objects which are capable to communicate with each other wirelessly in a smart environment have/had further increase the spectrum demand. In this paper, cognitive sensor network had been proposed to handle the loophole in the spectrum intelligently via spectrum sensing. In order to achieve a reliable spectrum sensing, an optimization scheme with fast convergence speed has been employed to optimize the sensing performance. The parameters of differential evolution have been set for solving the optimization problem in spectrum sensing for cognitive sensor network. The spectrum sensing formulation in cognitive sensor network has been modeled in MATLAB, and the optimization has been simulated using the differential evolution algorithm. The simulation result has shown that optimization using differential evolution approach has significantly increased the sensing performance which is an essential criterion for CSN which comply of many smart sensors that connect to each other wirelessly.