Spectrum Sensing and Channel Estimation in Cognitive Radio

International audience; The detection of signal presence is a crucial job carried out through spectrum sensing in cognitive radio systems. A tradeoff between detection accuracy and detector complexity is tackled often in researches. Amongst different spectrum sensing techniques, conventional energy detection is widely used due to its simplicity of implementation, however, it is sensitivity to noise variation makes it unreliable in low signal-to-noise-ratio environments. This manuscript proposes the use of scattering-based detector for spectrum sensing in the context of cognitive radio to provide reliable signal detection. Through scattering transform, signal features are enhanced whereas noise variations effects are reduced which enhances the detection results. The proposed detector is tested for chirp and spread spectrum signals in additive white Gaussian noise channel. Performance evaluation is conducted through calculation of detection probability for several signal-to-noise ratio values. Through MonteCarlo simulations, the proposed detector proves reliability of detection as compared to energy detection which provides false detection decision when noise only considered for detection.