lasseufpa/caviar: NTN use case

In this release, a Non-Terrestrial Network (NTN) is evaluated in the context of a search and rescue (SAR) scenario. Similar to the first use case described in 1, a drone operates in a disaster-stricken area, searching for individuals in need of rescue.

This iteration introduces several enhancements to the 3D simulation environment, leveraging Unreal Engine's Metahumans and additional assets such as vehicles (e.g., cars, trucks) to increase realism. The drone communicates with a core network node via a Low Earth Orbit (LEO) satellite link, modeled using an NTN-Urban stochastic channel. The network simulation is implemented using ns-3/5G-LENA.

The drone also transmits a video stream through the simulated network. This stream is accessible through a Grafana-based monitoring dashboard and is simultaneously used as input to a YOLOv8 AI model for real-time person detection.

Key features of this release include:

• Evaluation of Key Performance Indicators (KPIs), such as Round Trip Time (RTT), Throughput, and Signal-to-Interference-plus-Noise Ratio (SINR);
• AI-assisted human detection and rescue;
• Realistic video streaming traffic within the ns-3 simulation;
• Analysis of NTN channel performance in urban scenarios.