Research on Optimization of Unmanned Aerial Vehicle Communication Based on Wireless Communication Artificial Intelligence

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.

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Publication Details

Journal
ICST Transactions on Scalable Information Systems
Published
2025-07-04
DOI
https://doi.org/10.4108/eetsis.7695
Primary Topic
Innovative Educational Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on Optimization of Unmanned Aerial Vehicle Communication Based on Wireless Communication Artificial Intelligence

Yuqing Tang, Qiang Wang, Yu Geng
ICST Transactions on Scalable Information Systems
Innovative Educational Techniques
article

Research on Optimization of Unmanned Aerial Vehicle Communication Based on Wireless Communication Artificial Intelligence

Yuqing Tang, Qiang Wang, Yu Geng
article en

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.

ICST Transactions on Scalable Information SystemsVol. 12(3)
Shanghai Construction Group (China) (CN)
Government of Jiangsu Province
Openalex Percentile: Top 82%
Innovative Educational Techniques
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