用AI自适应调整无人机网络通信，降低数据包丢失率。
Traffic Simulation in Ad Hoc Network of Flying UAVs with Generative AI Adaptation
- 基于20架无人机构建自组网模型，研究传输功率与频段对通信影响。
- 实验显示：传输功率和频率变化显著影响数据包丢失率，且飞行区域与节点数也相关。
- 首次将AI动态调参融入无人机通信，适合智能交通与应急通信研究者。
本文旨在建模无人机自组网中的流量，并展示利用人工智能自适应调整通信信道的方法。模型基于包含20架无人机的原始自组网架构，分析了不同发射功率下数据包大小与丢包率的关系，不同频段下数据包大小与丢包率的关系，以及飞行区域和无人机数量对丢包的影响。程序代码实现了自适应数据传输方案，并展示了在人工智能自适应过程中，丢包率、功率与传输数据量随时间的变化关系。
原文摘要 · Abstract (English)
The purpose of this paper is to model traffic in Ad Hoc network of Unmanned Aerial Vehicles and demonstrate a way for adapting communication channel using Artificial Intelligence. The modeling was based on the original model of Ad Hoc network including 20 Unmanned Aerial Vehicles. The dependences of packet loss on the packet size for different transmission powers, on the packet size for different frequencies, on Unmanned Aerial Vehicles flight area and on the number of Unmanned Aerial Vehicles were obtained and analyzed. The implementation of adaptive data transmission is presented in the program code. The dependences of packet loss, power and transaction size on time during Artificial Intelligence adaptation are shown.
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