Description

Geo2SigMap is an efficient framework for high-fidelity RF signal mapping leveraging geographic databases, ray tracing, and a novel cascaded U-Net model. The project offers an automated and scalable pipeline that efficiently generates 3D building and path gain (PG) maps. The repository is split into two distinct partitions:

• Scene Generation: A pure Python-based pipeline for generating 3D scenes for arbitrary areas of interest.
• ML-based Propagation Model: ML-based signal coverage prediction using our pre-trained model based on the cascaded U-Net architecture described in ​this paper.

As of November 2025, v2.0.0 enhances the scene generation pipeline to include:

• LiDAR Terrain Data
• Building height calibration using Digital Elevation Models (DEMs)

This drastically improves the accuracy of the environment being processed by the ML-based Propagation Model or a ray tracer of your choice. Throughout the following notebook examples, we utilize Sionna RT. This package is open-source and highly accurate for generating coverage maps. If you are unfamiliar with Sionna RT, feel free to read Nvidia's ​Technical Report to better understand how it works. Tutorials for Sionna can be found [here ​https://nvlabs.github.io/sionna/rt/tutorials.html].

Prerequisites

To use Geo2SigMap with ease, we strongly suggest managing python packages using Anaconda. Anaconda's package manager, ​conda, offers everything you need with no extra configuration. It becomes extremely useful while running the notebook examples in the Demos section.

The installation process should ensure that all required packages are installed. In the event of any issue, this is the ​pipreqs list as of 1/21/2025:

osmnx >= 2.0.0
numpy
pyproj
shapely
rasterio
tqdm
pillow
open3d

Given the large overhead for ray tracing and ML tasks, access to a dedicated GPU is also suggested. Using Sionna RT with a CPU is limited and will restrict the possibilities

Package Installation

1. Create the Conda Environment:

conda create --yes --name g2sm --channel conda-forge pdal python=3.12
conda activate g2sm
pip install pyvista==0.45.2

If you opt not to use conda, please note the additional installation of pyvista v0.45.2

2. Clone and Install geo2sigmap:

git clone https://github.com/functions-lab/geo2sigmap
cd geo2sigmap/package
pip install .

The package is now installed and can be called via the CLI tool or using the Python function API.

Demos

Cite