Artificial Intelligence-Enabled UAV Communication Framework for Intelligent and Energy-Efficient Wireless Networks in Future 6G Systems

Abstract

ABSTRACT The rapid expansion of wireless communication services and the emergence of smart applications have created a growing demand for flexible, reliable, and high-capacity communication infrastructures. Conventional terrestrial communication networks often encounter challenges in providing continuous connectivity in disaster-stricken regions, remote locations, dense urban environments, and temporary large-scale events. Unmanned Aerial Vehicles (UAVs), commonly known as drones, have emerged as a promising solution for enhancing wireless communication networks due to their mobility, adaptability, and rapid deployment capabilities. UAV-assisted communication networks can function as aerial base stations, relays, data collectors, and mobile edge computing platforms, significantly improving network coverage, capacity, and service quality. This paper presents a comprehensive study of UAV-assisted communication systems and proposes an Artificial Intelligence-Enabled UAV Communication Framework (AI-UCF) designed to optimize aerial communication performance. The proposed framework integrates machine learning-based trajectory optimization, adaptive resource allocation, intelligent routing, and energy-efficient communication management. Simulation analysis demonstrates substantial improvements in coverage probability, throughput, latency, and energy efficiency compared with traditional communication architectures. The findings indicate that UAV-assisted communication networks will become a critical component of future 6G wireless infrastructures and intelligent networking ecosystems. Keywords— UAV Communication Networks, Drone Networks, Aerial Base Stations, 6G Wireless Systems, Artificial Intelligence, Mobile Edge Computing, Wireless Coverage, Intelligent Networking.