RayVerse

RayVerse is a large-scale urban radio propagation dataset generated via ray tracing, containing multipath propagation data (.propbin) and building geometry (.json) for 100 urban map scenarios. Each scenario includes multiple transmitter positions with full multipath information (path type, angle of arrival/departure, delay, path loss, etc.).

The dataset supports research on:

• Received Signal Strength (RSS) prediction
• Angular Power Spectrum (APS) estimation
• Power Delay Profile (PDP) analysis
• Antenna beam pattern evaluation

Download

The full dataset is available on Baidu Netdisk:

Link: https://pan.baidu.com/s/1Ze47tm5WohUUNBX8UUTQlg Password: vkm3

Repository Structure

RayVerse/
├── aps/                                    # APS visualization examples (PNG)
├── pdp/                                    # PDP visualization examples (PNG)
├── rss/                                    # RSS visualization examples (PNG)
└── src/
    ├── conversion/
    │   ├── propbin_to_aps_pdp.py           # Convert propbin to APS/PDP numpy arrays
    │   └── apply_sinc_beam.py              # Apply sinc antenna beam pattern to propbin
    ├── visualization/
    │   ├── visualize_rss.py                # Visualize a single RSS heatmap
    │   └── visualize_aps_pdp.py            # Visualize a single APS/PDP curve
    └── utils/
        ├── propbin_reader.py               # Read .propbin / .propbin.gz files
        └── propbin_writer.py               # Write .propbin v2 files

Dataset Format

The downloaded dataset has the following top-level structure:

RayVerse_data/
├── buildings_complete/                         # Building geometry for all maps
│   ├── 0.json
│   ├── 1.json
│   └── ...
├── map_0/
│   └── special_points_propbin_{FREQ}/          # e.g. special_points_propbin_3.5GHz
│       ├── source_0.propbin.gz                 # Multipath propagation data for TX 0
│       ├── source_1.propbin.gz                 # Multipath propagation data for TX 1
│       └── ...
├── map_1/
│   └── special_points_propbin_{FREQ}/
│       └── ...
└── ...

• {FREQ} is the carrier frequency used in ray tracing, e.g. 3.5GHz.
• Building geometry for map N is stored in buildings_complete/N.json.

The .propbin binary format stores per-path information including:

Field	Description
Path type	LoS, reflection, diffraction, etc.
AoD / AoA	Angle of departure / arrival (azimuth & elevation)
Delay	Propagation delay (ns)
Distance	Total path length (m)
Path loss	Per-path attenuation (dB)

Use src/utils/propbin_reader.py to load .propbin files in Python.

Quick Start

Read a propbin file

from src.utils.propbin_reader import load_propbin

data = load_propbin("map_0/special_points_propbin_3.5GHz/source_0.propbin.gz")

Visualize RSS heatmap

python src/visualization/visualize_rss.py \
    map_0/special_points_propbin_3.5GHz/source_0.propbin.gz --map-id 0

Convert to APS / PDP

python src/conversion/propbin_to_aps_pdp.py

Configuration (grid resolution, input/output paths) is set inside the script.

Apply antenna beam pattern

python src/conversion/apply_sinc_beam.py \
    --input-root /path/to/propbin_dir \
    --output-root /path/to/beamed_output \
    --map-id-start 0 --map-id-end 99 \
    --tx-boresight-az 0.0 \
    --tx-boresight-el 0.0 \
    --az-mainlobe-width 30.0 \
    --el-mainlobe-width 30.0

Visualize APS / PDP curves

python src/visualization/visualize_aps_pdp.py \
    --root /path/to/aps_pdp_dir \
    --name "aps_0_100_200_150_180"

Visualization Examples

Output filenames follow the convention below:

Type	Filename	Description
RSS	{map_id}_{tx_x}_{tx_y}.png	RSS heatmap for a given TX position
APS	aps_{map}_{src}_{tx_x}_{tx_y}_{rx}.png	Angular power spectrum for a TX-RX pair
PDP	pdp_{map}_{src}_{tx_x}_{tx_y}_{rx}.png	Power delay profile for a TX-RX pair

RSS Heatmap

Angular Power Spectrum (APS)

Power Delay Profile (PDP)

License

This dataset is released under the CC BY 4.0 License.