Efficient 3D-RSS map estimation method based on area classification

Abstract

We consider the determination of three-dimensional maps of received signal strength (3D-RSS maps) for disaster-recovery networks enabled by unmanned aerial vehicles (UAVs). In this paper, we extend the existing tensor completion based estimator to propose an efficient new 3D-RSS map estimator. To reduce the sensing route length for the UAV, the proposed method utilizes two approaches for estimating the RSS maps (the tensor completion-based and path-loss-based approaches), depending upon the number of high buildings. We show by simulation experiments that the proposed method can achieve a data-collection time comparable to those of existing methods with a shorter sensing route.