Hybrid architecture for spectrum sensing algorithm based on energy detection technique and artificial neural networks

Spectrum sensing is the critical application in cognitive radio which has been proposed in order to opportunistically benefit from the unused portions of the spectrum. It has shown that the detection of energy is the most convenient method, in the case where there is no a priori information about the primary user. In this work, the implementation of the energy detection technique has been done in MatLab for an AWGN channel, the simulation show that there are a lot of problems which decrease the performance of the energy sensor; it is susceptible to uncertainty in noise power and it cannot differentiate between primary user and the others cognitive users signal. In this respect, we propose in this paper, hybrid architecture which combines the simplicity of the energy detector, and the robustness of the artificial neural networks.