Back to datasets
Dataset assetOpen Source CommunityWireless CommunicationsSignal Processing

RadioMap_Dataset_Reflection/Scattering_Counts

The dataset was generated using the open‑source TensorFlow‑based library Sionna for ray‑tracing simulations, covering reflection and scattering counts across different urban areas in China. The simulated area is a 620‑meter square, with both transmitters and receivers positioned at a height of 1.5 m. The dataset includes raw simulation output files, RSSI grayscale images, transmitter location images, and scene images.

Source
github
Created
Jul 10, 2024
Updated
Jul 11, 2024
Signals
196 views
Availability
Linked source ready
Overview

Dataset description and usage context

RadioMap_Dataset_Reflection/Scattering_Counts

Dataset Overview

This dataset was produced by ray‑tracing (RT) simulations using the open‑source TensorFlow library Sionna. The simulation environment is based on various urban regions in China, focusing on a square area with a side length of 620 m. Transmitters (TXs) are uniformly distributed at a height of 1.5 m, and ground‑level receivers (RXs) are fixed at 1.5 m.

Simulation Parameters

  • Frequency: 2.5 GHz
  • Transmit Power: 23 dBm
  • Transmit Height: 1.5 m
  • Transmit Antenna Array: 8×4 elements, vertical and horizontal spacing 0.06 m (half‑wavelength), isotropic radiation pattern, dual‑polarized
  • Receive Height: 1.5 m
  • Receive Antenna Array: Single element, isotropic radiation pattern, cross‑polarized

Data Files

Scene_File

Contains 500 scene folders created and exported with Blender 3.6.

RadioMap_raw

Raw simulation output files generated by Sionna. Filenames range from 1_10.npy to 500_10.npy, indicating the scene number. Each file has a shape of 256×256×10×6, corresponding to (Rx_coordinates(i), Rx_coordinates(j), Tx_number, depth_max). Values represent RSSI. depth_max denotes the total number of reflections and scatterings; a depth_max of 0 indicates a scene without reflections or scatterings.

RSSI

Grayscale images derived from the RadioMap_raw files. Each point’s value is scaled to the range [0, 1] using the formula max{ (P_R - P_R,thr) / (P_R,max - P_R,thr) , 0 }, where P_R,max is the maximum received signal strength (‑13 dB) and P_R,thr is set to ‑70 dB. For example, 1_0_0.png represents the RadioMap for scene 1, TX 0, with depth_max = 0.

Tx

Grayscale images showing TX locations for each scene; pixel value 255 marks the TX position, all other values are 0. For instance, 1_0.png depicts the TX‑0 location in scene 1.

Scene

Grayscale images of the scenes obtained by a horizontal slice at 1.5 m through the 3D simulated environment. Pixel value 0 indicates building structures; all other values are 0.

Examples

Scene Images

Scene 1TX 1_0
scene_1.png1_0.png

RadioMap Images

RSSI 1_0_0RSSI 1_0_1RSSI 1_0_2
1_0_0.png1_0_1.png1_0_2.png
RSSI 1_0_3RSSI 1_0_4RSSI 1_0_5
1_0_3.png1_0_4.png1_0_5.png

In the examples, RSSI 1_0_0 denotes a scenario with no reflections or scatterings, RSSI 1_0_1 indicates a single reflection/scattering event, and so on.

Future Updates

Datasets with additional TX data for each scene are in preparation and will be released soon.

Need downstream help?

Pair the dataset with AI analysis and content workflows.

Once the source passes your review, move straight into summarization, transformation, report drafting, or presentation generation with the JuheAI toolchain.

Explore AI studio