INNOVATIVE MODELING AND ANALYTICAL APPROACH FOR ENHANCING COMMUNICATION EFFICIENCY IS BASED ON AERIAL AD HOC NETWORKS

Document Type : Original Article

Authors

1 Dept. of Electronics & Comm., Egyptian Air Defense College

2 Computer and systems Engineering Department - faculty of engineering - Mansoura university - Egypt

3 Computers and Control Dept. Faculty of Engineering, Mansoura University, Mansoura, Egypt

4 Computers and Control Systems Engineering Department, faculty of engineering Mansoura University, Mansoura, Egypt

Abstract

Abstract: Aerial Ad Hoc Networks (AANET) connect devices and aerial platforms without a network, drawing interest. These platforms have different goals but need communication infrastructure. Mobility and poor power supply management are particular to these networks and devices. The study shows a user-friendly, adaptable technique. Changing communication network designs and using UAV-mounted base stations enhances results. This role involves selecting station sites in the case of a communications network collapse due to an incident, natural disaster, or technical failure and determining the financial and logistical requirements for aircraft. Game theory and drone communication helped us examine and solve the situation according to its complexities. The simulation covered all possible outcomes after the communication network tower failed. The study recommends creative disaster communication methods: The study encourages faster and more flexible emergency drone-mounted base station deployment. Natural disasters, technology failures, and other events reconstruct communication networks. Innovative drone deployment optimization using game theory across fields achieves this. The article specifies drone base station locations for optimal connectivity. Drone numbers depend on economic or humanitarian requirements, cost-effectiveness, and emergency reaction. Prioritizing network restoration after disasters enhances crisis management and recovery. Using game theory to build drone communication networks is innovative. Our method increased average throughput by 48.4% and user coverage by 36.7% over random deployment while reducing reaction time compared to fixed-cell options.

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