GLRT-based spectrum sensing by exploiting Multitaper Spectral Estimation for cognitive radio network

Abstract

Spectrum sensing is a key technique for future intelligent networks, such as AdHoc network, wireless sensor networks. However, the existing works suffer from high computational complexity, which is a huge challenge for those networks composed of many nodes with the limited computing capabilities. In this paper, we propose a simple and novel method based on the generalized likelihood ratio test(GLRT) criterion and offer a specific algorithm based on maximum value of power spectrum calculated by multitaper spectral estimation. We first derive the statistical characteristics and probability density function of test statistic, and the closed-form expression of detection probability and false-alarm probability are obtained. Then, we carry out some simulations to verify the proposed algorithm by taking BPSK signal as an example. In the simulations, we compare the sensing performance between the proposed algorithm and the existing methods. Both theoretical analysis and simulation results demonstrate the advantages of the proposed algorithm over the existing methods.