OpenPathNet Dataset

This README describes the OpenPathNet dataset (the release referred to as Link 1 in the OpenPathNet project documentation). The dataset is generated by the OpenPathNet toolchain from real-world Miami and Boston urban areas based on OpenStreetMap (OSM), and then simulated with NVIDIA Sionna ray tracing for RF multipath propagation / channel modeling research and AI tasks.

The dataset is also carefully cleaned to ensure good building coverage in every scene.

• Project code / generator repository: https://github.com/liu-lz/OpenPathNet
• City subsets: Miami (806 scenes) and Boston (971 scenes) (same directory layout across cities)

Directory Structure

.
├── Miami/
│   ├── scenes/
│   │   └── scene_<lat>_<lon>/
│   │       ├── scene.xml
│   │       └── mesh/
│   │           ├── building_*.ply
│   │           └── ground.ply
│   ├── raytracing_results/
│   │   └── scene_<lat>_<lon>/
│   │       ├── raytracing_results.csv
│   │       ├── raytracing_results.pkl
│   │       ├── deepmimo_format.npy
│   │       ├── channel_gain_distribution.png
│   │       ├── delay_distribution.png # Here “delay” refers to ToA (Time of Arrival); the latest OpenPathNet fixes this filename
│   │       ├── path_type_distribution.png
│   │       ├── outdoor_receivers.png
│   │       └── heatmaps/
│   │           ├── azimuth_heatmap.png
│   │           ├── channel_gain_heatmap.png
│   │           ├── delay_heatmap.png  # Here “delay” refers to ToA (Time of Arrival); the latest OpenPathNet fixes this filename
│   │           └── elevation_heatmap.png
│   ├── generated_scenes.txt
│   └── raytracing.log
├── Boston/
│   └── ... (same structure as Miami)
└── README.md

Naming

• Each scene directory is named scene_<lat>_<lon>, where <lat> / <lon> are decimal latitude/longitude.
• Scene folders under scenes/ and raytracing_results/ correspond one-to-one.

Files

generated_scenes.txt

A generation manifest and metadata (tabular text).

• The header records the total count, center coordinate, sampling radius, scene size, generation mode, etc.
• Each (tab-separated) row includes:
  • Scene file path (e.g., data\scenes\scene_...\scene.xml)
  • Original / actual latitude & longitude
  • Generation type (e.g., OSM)
  • Attempts
  • Offset distance (km)

raytracing.log

A summary log for batched ray tracing (typically one line per scene), including runtime, number of receivers, and number of paths.

scenes/

Geometry assets for each scene.

• scene.xml: scene description file (digital-twin / renderer-compatible format).
• mesh/: geometry meshes (e.g., buildings and ground) in .ply.

raytracing_results/

Ray-tracing outputs and visualizations for each scene.

For each receiver point in each scene, this dataset keeps and records the top 5 paths with the highest channel gain. The files below contain the full multipath attributes for those retained paths, including receiver location, carrier frequency, path type, channel gain, ToA (Time of Arrival), and departure/arrival angles.

• raytracing_results.csv: tabular results (easy to analyze/import).
• raytracing_results.pkl: Python-serialized results (fast loading).
• deepmimo_format.npy: DeepMIMO-style structured output for downstream ML pipelines.
• heatmaps/ and *.png: visualizations (e.g., channel gain / delay(ToA) / azimuth / elevation).

Data schema: raytracing_results.csv / raytracing_results.pkl

• Structure: tabular data; typically one row = (receiver rx_id, one path), so each rx_id usually appears 5 times.
• raytracing_results.pkl is a pandas.DataFrame with the same columns as raytracing_results.csv.

Columns:

• rx_id: receiver index (integer).
• type: path type (e.g., LoS / Reflected / Scattered).
• channel_gain: channel gain-related numeric value (scientific notation).
• tau: ToA (Time of Arrival) in seconds.
• freq: carrier frequency in Hz.
• rx_coord: receiver coordinates, formatted as a string like "[x, y, z]".
• phi_r, theta_r: AoA azimuth / elevation angles.
• phi_t, theta_t: AoD azimuth / elevation angles.

Data schema: deepmimo_format.npy

• File content: a scalar numpy.ndarray with dtype=object; arr.item() yields a dict.
• Top-level keys:
  • user: a list of length $N_{rx}$; each element corresponds to one receiver.
  • location: a list used to describe scene / coordinate system information (may vary slightly across versions/configs).

Each user[i] is a dict containing:

• location: numpy.ndarray of shape (3,), receiver coordinates [x, y, z].
• paths: a dict containing (arrays are length 5, i.e., Top-5 paths):
  • channel_gain: float32, shape (5,)
  • ToA: float32, shape (5,)
  • DoA_theta: float64, shape (5,)
  • DoA_phi: float64, shape (5,)
  • num_paths: int (5 in this dataset)

Reproducibility / Regeneration

This dataset is generated by the OpenPathNet toolchain. For generation scripts, ray-tracing entry points, and system requirements, please refer to:

• https://github.com/liu-lz/OpenPathNet

Citation

If you use OpenPathNet in your research, please refer to the citation information in the OpenPathNet repository documentation.

License & Notes

• This directory contains a dataset slice/subset. For licensing, the generator code license, and third-party data source statements (OSM, etc.), please follow the OpenPathNet repository documentation.