Multiple-Antenna-Based Blind Spectrum Sensing in the Presence of Impulsive Noise

Cognitive radio (CR) was proposed as a solution to the spectrum scarcity problem. One of the basic functions of any CR is spectrum sensing. Most existing works on spectrum sensing consider the Gaussian noise assumption. In practice, this assumption is not always valid since several existing noise types exhibit non-Gaussian and impulsive behavior. Hence, it is very beneficial to study spectrum sensing in the presence of impulsive noise. In this paper, we propose two new multiple-antenna-based spectrum sensing methods, assuming that the underlying noise follows a symmetric α-stable distribution. This assumption is justified by a distribution fitting of some measurements of the noise acting on the GSM-R antennas onboard trains. The first proposed sensing method is based on the covariation properties of α-stable processes, whereas the second proposed method has the strategy of filtering the corrupted signals before applying a traditional spectrum sensing method. These two methods do not require a priori knowledge about the primary-user signal. Simulation results show that the proposed algorithms provide good spectrum sensing performance in the presence of α-stable distributed impulsive noise.