Kriging-Based 3-D Spectrum Awareness for Radio Dynamic Zones Using Aerial Spectrum Sensors

Abstract

Radio dynamic zones (RDZs) are geographical areas within which dedicated spectrum resources are monitored and controlled to enable the development and testing of new spectrum technologies. Real-time spectrum awareness within an RDZ is critical for preventing interference with nearby incumbent users of the spectrum. In this article, we consider a 3-D RDZ scenario and propose to use unmanned aerial vehicles (UAVs) equipped with spectrum sensors to create and maintain a 3-D radio map of received signal power from different sources within the RDZ. In particular, we introduce a 3-D Kriging interpolation technique that uses realistic 3-D correlation models of the signal power extracted from extensive measurements carried out at the NSF Aerial Experimentation and Research Platform for Advanced Wireless (AERPAW) platform. Using C-band signal measurements by a UAV at altitudes between 30 and 110 m, we first develop realistic propagation models on airto-ground path loss, shadowing, spatial correlation, and semi-variogram, while taking into account the knowledge of antenna radiation patterns and ground reflection. Subsequently, we generate a 3-D radio map of a signal source within the RDZ using the Kriging interpolation and evaluate its sensitivity to the number of measurements used and their spatial distribution. Our results show that the proposed 3-D Kriging interpolation technique provides significantly better radio maps when compared with an approach that assumes perfect knowledge of path loss. Specifically, the root-mean-square error (RMSE) of the signal power prediction achieved by our proposed 3-D Kriging method is notably lower compared to that of the perfect path loss-based prediction, especially when the height difference between measured and the target locations is less than 20 m.