3D REM-based Positioning Procedure for UAV-Assisted Het-Nets

The recent advances in wireless communications toward upcoming services and infrastructure have spurred the development of unmanned aerial vehicle (UAV) assisted terrestrial networks. They offer the prospect of significant capacity improvement through the aerial base station (ABS), particularly when it leverages three-dimensional (3D) radio environment maps (REMs) that provide spectrum occupancy characterization. The heterogeneous network (Het-Net) with an ABS scenario consists of a stationary ground base station (GBS), an ABS and mobile users. Motivated by the 3D REMs’ potential and their limited application in the field, this work introduces a heuristic procedure for ABS positioning that integrates the collection of received signal strength (RSS) measurements to update the REM, Kriging-based 3D REM reconstruction, and user association with the ABS. The experiments determine the 3D REM sampling rate and, consequently, the amount of necessary measurements, based on the highest achievable system capacity. In addition, this novel solution is compared to reference methods for UAV positioning through extensive simulations, showing an increase of up to 15% compared to alternative algorithms, reaching a maximum capacity of 128 Mbps.