scalable drone networks

: Background: Unmanned aerial vehicle (UAV) networks as an important part of the modern telecommunication are gaining importance in various situations, including rural coverage, urban settings and emergency situations. However, Interference, scalability and energy efficiency still pose problems to the advancement of wireless networks. Objective: The aim of current study is to integrate and assess an adaptive frequency management technique for improving the performance of communication networks involving UAVs in terms of interference, transmission rates, and reliability within different deployment settings. Methods: Experimental and simulated studies were performed to evaluate the effectiveness of the algorithm in this combination. Performance measurements in terms of latency, throughput, packet loss, energy consumption and signal strength were made under rural, urban and emergency conditions. The adaptable algorithm used certain working frequencies depending on the interferences present and the network performance parameters recorded. Results: The algorithm showed very distinct enhancements in all models and positions, decreasing latency by 20.5%, enhancing throughput by 14.5%, and decreasing the packet loss by 57.6% in the urban site settings. Other executed experiments documented improved energy efficiency and communication reliability in rural and emergency situations. Conclusion: The adaptive frequency management algorithm proposed by the authors effectively solves significant issues of critical concern in UAV networks while offering robust scalability for next-generation telecommunications infrastructure. The future research recommendation incorporates the combination of the proposed optimization with other complementary approaches and/or the testing of the developed system at more severe actual conditions.