Probabilities of detection and false alarm in multitaper based spectrum sensing for cognitive radio systems in AWGN

The paper presents closed-form expressions for the detection, and false alarm probabilities for spectrum sensing detection in Additive White Gaussian Noise (AWGN) based on the Multitaper Spectrum Estimation Method (MTM) using Neyman-Pearson criterion. The MTM spectrum sensing is a powerful technique in Cognitive Radio (CR) systems. It tolerates problems related to bad biasing, and large variance of estimates, that are the main drawbacks in the periodogram (energy detector). The performance of the MTM spectrum sensing system is controlled by parameters, such as the chosen half time bandwidth product, Discrete Prolate Slepian Sequence (DPSS) (i.e., tapers), DPSS' eigenvalues, and the number of tapers used. These parameters determine the theoretical probabilities of detection and false alarms, which are used to evaluate the system performance. The paper shows a good match between the theoretical and numerical simulation results.