Spectrum sensing based on normality test

This paper presents an analysis of spectrum sensing to determine if a signal, measured by a cognitive user in an AWGN channel, is a valid one, from the primary user, or if it is composed of noise alone. The proposed method for spectrum sensing is based on statistical tests to identify if the probability distribution of the received signal has noise characteristic, or other distribution that classifies it as a primary user. The results of Monte-Carlo simulations indicate that it is possible to identify transmission opportunities using spectrum sensing tests with low signal-to-noise ratio.