Cognitive Radio: A Gram-Charlier based Non-parametric Approach in the Context of Spectrum Hole Search

Cognitive radio arises to be tempting solution to the spectral congestion problem by introducing opportunistic usage of the frequency bands that are not heavily occupied by licensed users. Spectrum sensing plays a crucial role in the cognitive radio technology to prevent damaging interference to the primary users and to reliably and quickly spot the white spaces in the spectrum and utilize the opportunity. In energy detection based spectrum sensing technique, the noise distribution as well as the signal plus noise distribution is assumed to be Gaussian. In reality, however, it is often difficult to validate these underlying assumptions with the available data. In this paper, an approach has been made by considering signal plus noise distribution as non-Gaussian and approximated with the generalized Gram-Charlier Type A series. The probability of detection is given for Gram-Charlier series for a fixed false alarm probability.