UAV Mobile Channel Adaptation Using AI

The aim of this work is to implement the adaptation of Unmanned Aerial Vehicle (UAV) communication channel using Artificial Intelligence (AI). Simulation was provided on the base of original model for communication channel “Ground Control Station – Satellite Transponder – Aerial Relay Drone – UAV”, which was designed using MATLAB Simulink software. Dependences of the Bit Error Rate (BER) on Signal-to-Noise Ratio (SNR) for different data rates, BER on Ground Control Station antenna diameter and BER on “Satellite Transponder” and “Aerial Relay Drone” amplifiers nonlinearity were obtained and analysed. The program code for training a linear regression model for predicting BER based on the obtained data is presented. The trained model adaptively changes SNR to find the optimal value at different Data Rates. The BER, SNR, and Data Rate dependences on time during channel adaptation are plotted.