CWT based improved approach to wideband spectrum sensing for cognitive radios

Cognitive radio has become into a matter of great interest now-a-days for researchers as it opens a wide horizon of opportunities for maintaining the exponentially increasing bandwidth demand. In cognitive radio networks, Spectrum sensing is a major concerning issue for exploring dynamic spectrum management. This paper introduces an improved but simple continuous wavelet transform(CWT) based approach for efficient spectrum sensing of wideband channel, based on edge detection in which soft de-noising is utilized to suppress the noise level. One special feature of our approach is to use single scale transformation unlike most of the edge detection approach involves multi-scale transforms or product to suppress the noise as well as to detect edges properly which indicates frequency boundaries and identification of these edges is shown through simulation results. Performance of detection in low SNR region by our proposed method has also been improved than the conventional methods which is also illustrated through simulation result.