Optimal field measurement design for radio environment mapping

Abstract

White spaces are locally or temporally available frequencies that are principally reserved for primary use such as TV broadcasting. The currently prevalent view to the utilization of such spectrum resources is that white space devices must query a geolocation database to obtain information about available frequencies and related maximum transmission powers. A geolocation database is fundamentally based on field strength estimates of the primary service obtained using radio propagation models. However, field strength estimates for geographically extensive broadcast networks are typically computed for spatial resolutions of hundreds of square meters. Therefore, even with the most sophisticated propagation models currently available, the predicted values always contain errors due to the limited geographical information. To overcome such deficiency, we propose a geostatistical approach for estimating the radio environment based on universal kriging interpolation. In addition, we optimize the locations of field measurements using spatial simulated annealing, and show that it improves significantly local field strength estimates.

Designing a Testbed Infrastructure for Experimental Validation and Trialing of 5G Vertical Applications

“…Turku TVWS test environment [16] was set up during in White Space Test Environment for Broadcast Frequencies (WISE), WISE2 and ReWISE (Reliability Extension to White Space Test Environment) projects (2011-2014) [17] to develop and validate technical solutions, accelerate commercial utilization of white spaces, and to contribute to the regulation and standardization work [18,19,20,21,22,23,24,25,26,27,28,29]. The test network and associated radio laboratory are located in Turku, Finland.…”

Heuristic approach for forecast scheduling

“…Several works ( [6], [7], [8]) have considered the geostatistical interpolation technique known as Kriging [9] to build REMs. This technique exploits the spatial correlation of the signal propagation to provide higher prediction accuracy than classical propagation models.…”

Optimal visualization design for electromagnetic environment situation of the sea

“…In [3], a new method has been described to implement the visualization of two-dimensional static electromagnetic situation by using Delaunay triangles. In cognitive radio, researches in [4]- [6] focus on sampling method and interpolation method in order to arrange the position of the receivers for estimating the radio environment map of the observed area to minimize the cost. In [7]- [9], three simulation methods of the complex electromagnetic environment have been proposed by using three corresponding particular computing platforms.…”