  A new spectrum sensing detector is proposed and analytically studied, when it
operates under generalized noise channels. Particularly, the McLeish
distribution is used to model the underlying noise, which is suitable for both
non-Gaussian (impulsive) as well as classical Gaussian noise modeling. The
introduced detector adopts a moment-based approach, whereas it is not required
to know the transmit signal and channel fading statistics (i.e., blind
detection). Important performance metrics are presented in closed forms, such
as the false-alarm probability, detection probability and decision threshold.
Analytical and simulation results are cross-compared validating the accuracy of
the proposed approach. Finally, it is demonstrated that the proposed approach
outperforms the conventional energy detector in the practical case of noise
uncertainty, yet introducing a comparable computational complexity.
