Traffic Simulation in Ad Hoc Network of Flying UAVs with Generative AI Adaptation
This addresses communication reliability in UAV networks, but it is incremental as it applies existing AI methods to a specific simulation scenario.
The paper models traffic in an ad hoc network of 20 UAVs and demonstrates adaptive communication channel control using AI, showing dependencies of packet loss on parameters like packet size, transmission power, frequency, flight area, and number of UAVs, with results including packet loss, power, and transaction size over time during AI adaptation.
The purpose of this paper is to model traffic in Ad Hoc network of Unmanned Aerial Vehicles and demonstrate a way for adapting communication channel using Artificial Intelligence. The modeling was based on the original model of Ad Hoc network including 20 Unmanned Aerial Vehicles. The dependences of packet loss on the packet size for different transmission powers, on the packet size for different frequencies, on Unmanned Aerial Vehicles flight area and on the number of Unmanned Aerial Vehicles were obtained and analyzed. The implementation of adaptive data transmission is presented in the program code. The dependences of packet loss, power and transaction size on time during Artificial Intelligence adaptation are shown.