Evaluation of kriging interpolation methods as a tool for radio environment mapping

Abstract

In the journey toward optimal spectrum usage, techniques and concepts such as Cognitive Radio and Dynamic Spectrum Access have enjoyed increasing attention in many research projects. Dynamic Spectrum Access introduces the need for real-time RF spectrum information in the form of Radio Environment Maps. This need motivates an investigation into a hybrid approach of sample measurements and spatial interpolation as opposed to using conventional propagation models. Conventional propagation models, both path-general and path-specific, require information of transmitters within the area of interest. Irregular Terrain Models such as the Longley-Rice model, further require topographic information in order to consider the effects of obstacles. The proposed spatial interpolation technique, kriging, requires no information regarding transmitters. Furthermore, Ordinary Kriging requires nothing other than measured samples whereas other kriging variants such as Universal Kriging and Regression Kriging can use additional information such as topographic data to aid in prediction accuracy. This dissertation investigates the performance of the three aforementioned kriging variants in producing Radio Environment Maps of received power. For practical and financial reasons, the received power measurement samples are generated using the Longley-Rice Irregular Terrain Model and are, therefore, simulated measurements. The experimental results indicate that kriging shows great promise as a tool to generate Radio Environment Maps. It is found that Ordinary Kriging produces the most accurate predictions of the three kriging methods and that prediction errors of less than 10 dB can be achieved even when using very low sampling densities.