Research Article
Research on Optimization of Unmanned Aerial Vehicle Communication Based on Wireless Communication Artificial Intelligence
@ARTICLE{10.4108/eetsis.7695, author={Yu Geng and Yuqing Tang and Qiang Wang }, title={Research on Optimization of Unmanned Aerial Vehicle Communication Based on Wireless Communication Artificial Intelligence}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={12}, number={3}, publisher={EAI}, journal_a={SIS}, year={2025}, month={7}, keywords={Communication, Surveillance, Inconvenient, Latency, Application}, doi={10.4108/eetsis.7695} }- Yu Geng
Yuqing Tang
Qiang Wang
Year: 2025
Research on Optimization of Unmanned Aerial Vehicle Communication Based on Wireless Communication Artificial Intelligence
SIS
EAI
DOI: 10.4108/eetsis.7695
Abstract
In the last few years, there has been an increasing use of Unmanned Aerial Vehicles (UAVs), leading to a demand for robust and efficient communication technologies. But by their nature, UAVs operate dynamically and relatively sparsely in the sky, making it inconvenient to perform traditional communication. To overcome communication hurdles, the authors of this research propose an AI approach to optimize wireless communications to enhance UAV (Unmanned Aerial Vehicles) performance. The study will investigate the development of an AI-based algorithm to adjust communication parameters concerning various aspects, including UAV movement, environmental conditions, and network constraints. It will increase the data transmission quality, reduce latency, and service larger areas the network covers for UAVs. Simulations and actual world experiments will be conducted to evaluate the proposed approach, showing that AI can enhance UAV communication. This work could significantly improve the performance of UAVs and optimize their application in many fields ranging from surveillance to delivery services.
Copyright © 2025 Y. Geng et al., licensed to EAI. This open-access article is distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transforming, and building upon the material in any medium so long as the original work is properly cited.
