Adaptive Multiple Input Multiple Output Antennas for Unmanned Aerial Vehicle and Drone-Based Communication in Dynamic Environments

This paper investigates the performance of an Adaptive Kalman Filter-based Multiple Input Multiple Output (MIMO) beam forming technique for Unmanned Aerial Vehicle (UAV) communications. The adaptive beam forming technique was implemented to improve signal quality and tracking accuracy in dynamic communication channels, which are characterized by time-varying channel conditions driven by UAV mobility. A comprehensive analysis was conducted in MATLAB, where the proposed system was compared with traditional fixed beam forming. The results reveal a significant improvement in Bit Error Rate (BER) for the adaptive beam forming system. Specifically, the average BER for the fixed beam forming system is found to be 0.115, whereas the adaptive system reduces the BER to 0.012, demonstrating a 10× reduction in error rate. Additionally, the channel capacity increases from an average of 5.2 bps/Hz for fixed beam forming to 6.8 bps/Hz for the adaptive beam forming system, which corresponds to a 30% increase in spectral efficiency. The adaptive Kalman Filter-based beam forming system offers substantial improvements across all performance parameters, making it a potential solution for reliable UAV communications in dynamic, interference conditioned environments.