A Comparative Study of the Computation Efficiency of a GPU-Based Ray Launching Algorithm for UAV-Assisted Wireless Communications

Abstract

Graphics Processing Units (GPU), have opened up new opportunities for speeding up general-purpose parallel computing applications. In this paper, we present the computation efficiency in terms of time performances of a novel ray launching field prediction algorithm which relies on NVIDIA GPUs and its Compute Unified Device Architecture (CUDA). The software tool assesses the propagation losses between a wireless transmitter - carried by an Unmanned Air Vehicle (UAV) - over a 3D urban environment. Together with other effective features, the software tool is shown to reduce by several orders of magnitude the computation time of simulations. Performances and cost-benefit analysis of three different NVIDIA GPU configurations are thus investigated over three different urban scenarios, taken as test-cases for Air-to-Ground (A2G) communications for 5G applications and beyond.