An Efficient Spectrum Sensing and Matched Filter Interference Modelling In Cognitive Radio Network

Cognitive radio is an effective approach for better sharing the underutilized communication spectrum. That underutilized frequency bands have been licensed to the primary users. However due to the uncertainity in detecting the existence of the primary user, the secondary user may interfere with the primary user. When both primary user and secondary users are active simultaneously. Therefore understanding the interference and its consequences on the cognitive network is critical. Unlike statistical models previously reported in the literature minimizing the interference using solid mathematical analysis. We propose an accurate model for describing the interference with amplitude, frequency, mean and variance of the interference suffered by the primary user. The proposed model sense accurately the spectrum using maximum to minimum eigen value technique in the sensing scheme, and we use tracy widom approach. For removing the interference at the receiving section a matched filter is introduced at the output. Simulation results are provided to verify the effectiveness of the model.