# Traffic Simulation in Ad Hoc Network of Flying UAVs with Generative AI Adaptation

arXiv: https://arxiv.org/abs/2602.13200 · HTML: https://mlsanity.com/paper/2602.13200/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 19 references that are in the map.
- First posted on arXiv 1 Jan 2026.

## Builds on (most cited first, 2 of 2)

- [Generative AI for Advanced UAV Networking](https://mlsanity.com/paper/2404.10556/) (2024)
- [Generative Neural Network Channel Modeling for Millimeter-Wave UAV Communication](https://mlsanity.com/paper/2012.09133/) (2020)

## Abstract (arXiv)

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.