Volume 13, Number 2

Developing an Adaptive Channel Modelling using a Genetic Algorithm Technique to Enhance Aerial Vehicle-to-Everything Wireless Communications


Faris. A. Almalki, Taif University, Kingdom of Saudi Arabia


In this digital era, Internet of Everything (IoE) has a potential to bring out drastic changes to how we live today, where billions of people and devices require wireless connectivity. Where Unmanned Aerial Vehicles contribute positively in paving the way for IoE and Fifth Generation technologies, and tackle some of their comms challenges. Thus, this paper aims to provide an adaptive approach using a Genetic Algorithm (GA) technique by combining indoor and outdoor propagation models to enhance aerial vehicle-to-everything wireless connectivity. The proposed adaptive approach uses a GA multi-objective function that yield optimum values of UAV altitude, elevation angles, and type of building for indoor environment. The proposed GA optimization technique has met the demand of a typical dense-populated urban environment, as well as empowering the IoE with greater coverage footprint, high Quality of Service benchmark, and line-of-sight adaptability. The output results emphasized that the proposed adaptive approach using the GA technique can help in smart decision-making and selecting a proper setup and find the optimum parameters to provide seamless wireless connections from aerial vehicle-to-everything.


Unmanned Aerial Vehicles, Internet of Everything, Channel Modelling, Propagation Model, Fifth Generation.