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

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.