Cognitive radios (CRs) have been proposed as a possible solution to improve spectrum utilization by enabling opportunistic spectrum sharing. The main requirement for allowing CRs to use licensed spectrum on a secondary basis is not causing interference to primary users. Spectrum sensing allows cognitive users to autonomously identify unused portions of the radio spectrum, and thus avoid interference to primary users. In this work, energy detection technique is considered for spectrum sensing, and the performance evaluation of an energy detector is presented. The process of threshold selection for energy detection is addressed by the Constant False Alarm Rate (CFAR) method and selection is carried out considering present conditions of noise levels. Our results show that if we dynamically adjust detection-threshold based to the noise level present during detection process, the detection probability will be higher than the one obtained when a fixed threshold value is considered

This paper introduces the design of sparse concentric rings array for isoflux coverage to Earth surface over a visibility cone of more than 100°. This design of concentric rings antenna array considers the optimization of the angular separation between the antenna elements and the amplitude excitation across the array in order to generate the characteristics of the desired isoflux radiation. Simulation results using an evolutionary multi-objective optimization method are provided in this document. Furthermore, an analysis of several design cases of sparse concentric rings array for wide isoflux patterns considering a different number of antenna elements for Low Earth Orbit satellites is achieved.

In this work, the authors present the evaluation of energy detection (ED) based on the Welch's periodogram for spectrum sensing applied to cognitive radio networks. The authors analyse the impact of the number of points in the discrete Fourier transform and the number of averaged periodograms for power density spectrum estimation on the performance of ED. The authors identify that the inclusion of these parameters in the distribution of the test statistic used to detect the presence of primary users, improves the probability of detection. However, in the presence of noise uncertainty, the improvement on the probability of detection will come at the expense of an increased probability of false alarm. With the approach considered in this work is possible to increment the probability of detection for a given and low signal‐to‐noise ratio, without increasing the number of samples collected from primary signal. However, to maintain a constant probability of false alarm, accurate techniques for noise variance estimation are needed, because detection‐threshold value is highly dependent on the noise power present at each sensing interval.