---
language:
- en
license: cc-by-4.0
size_categories:
- 10K<n<100K
task_categories:
- image-to-image
pretty_name: Multi-config Radiomap Dataset and Pretrained Models for U6G XL-MIMO
tags:
- wireless
- radiomap
- xl-mimo
- u6g
- beamforming
- benchmark
- signal-processing
---

# Multi-config Radiomap Dataset and Pretrained Models for U6G XL-MIMO

This repository provides the **public release of the Multi-config Radiomap Dataset and pretrained models** for **U6G / XL-MIMO radiomap prediction**.

It includes:
- a large-scale radiomap dataset across **800 urban scenes**
- multiple frequency bands and array configurations
- beam-map-related benchmark resources
- pretrained models for benchmark tasks

## Links

- **Paper:** https://arxiv.org/abs/2603.06401
- **Project Website:** https://lxj321.github.io/MulticonfigRadiomapDataset/
- **Code Repository:** https://github.com/Lxj321/MulticonfigRadiomapDataset
- **Dataset + Pretrained Models:** this Hugging Face repository

## Contents

### Files in this repository

- `Dataset_*.zip`  
  Main dataset package, including radiomap-related data and associated resources.

- `Pretrained_Model_*.zip`  
  Pretrained models for benchmark tasks.

- `metadata.csv`  
  Lightweight metadata index for preview and quick inspection.

## Dataset Summary

This project is designed for studying:
- multi-configuration radiomap prediction
- cross-configuration generalization
- cross-environment generalization
- beam-aware radiomap modeling
- sparse radiomap reconstruction

### Quick facts

- **Scenes:** 800
- **Frequency bands:** 1.8 / 2.6 / 3.5 / 4.9 / 6.7 GHz
- **TX antenna scale:** up to 32x32 UPA
- **Beam settings:** 1 / 8 / 16 / 64 beams

## Visual Examples

Representative examples from the released dataset are shown below.

### Overview

This figure shows an overall preview of the released data components, including the height map, ray-tracing radiomap, and configuration-only beam map.

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/homepage_teaser.png" width="88%">
</p>

### Radiomap Examples

Representative ray-tracing radiomap examples from different scenes and configurations.

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/radiomaps_grid.png" width="88%">
</p>

### Height Map Examples

Representative height map examples from the released urban scenes.

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/height_maps_grid.png" width="88%">
</p>

### Beam Map Examples

Representative configuration-only beam map examples.

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/beam_maps_grid.png" width="88%">
</p>

### Paired Examples

The following examples illustrate the correspondence among the released data components for selected scenes and transmitter configurations.

#### Example 1

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/paired_examples/u9__freq_6.7GHz_64TR_8beams_pattern_tr38901__beam07.png" width="95%">
</p>

#### Example 2

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/paired_examples/u100__freq_6.7GHz_1024TR_64beams_pattern_tr38901__beam41.png" width="95%">
</p>

#### Example 3

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/paired_examples/u460__freq_6.7GHz_256TR_16beams_pattern_tr38901__beam00.png" width="95%">
</p>

#### Example 4

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/paired_examples/u100__freq_1.8GHz_16TR_1beams_pattern_tr38901__beam00.png" width="95%">
</p>

#### Example 5

<p align="center">
  <img src="https://raw.githubusercontent.com/Lxj321/MulticonfigRadiomapDataset/main/docs/assets/dataset/paired_examples/u461__freq_6.7GHz_1024TR_64beams_pattern_tr38901__beam16.png" width="95%">
</p>

## Intended Usage

This dataset is intended for:
- benchmark evaluation of radiomap prediction methods
- studying generalization across unseen array configurations
- studying generalization across unseen environments
- evaluating physics-informed features such as beam maps
- reproducing the results of the associated benchmark project

## Download and Usage

Download the released zip packages from the **Files and versions** tab.

For code, preprocessing, training, evaluation, and benchmark usage, please refer to:
- **GitHub:** https://github.com/Lxj321/MulticonfigRadiomapDataset
- **Project Website:** https://lxj321.github.io/MulticonfigRadiomapDataset/

## Repository Structure

The released resources are organized around:
- dataset files
- pretrained model files
- project documentation
- benchmark code in the GitHub repository


## Download and Usage

Download the released zip packages from the **Files and versions** tab.

For code, preprocessing, training, evaluation, and benchmark usage, please refer to:
- **GitHub:** https://github.com/Lxj321/MulticonfigRadiomapDataset
- **Project Website:** https://lxj321.github.io/MulticonfigRadiomapDataset/

## Repository Structure

The released resources are organized around:
- dataset files
- pretrained model files
- project documentation
- benchmark code in the GitHub repository

## Citation

If you use this dataset or the pretrained models, please cite the associated project and paper.

```bibtex
@misc{li2026u6gxlmimoradiomapprediction,
      title={U6G XL-MIMO Radiomap Prediction: Multi-Config Dataset and Beam Map Approach}, 
      author={Xiaojie Li and Yu Han and Zhizheng Lu and Shi Jin and Chao-Kai Wen},
      year={2026},
      eprint={2603.06401},
      archivePrefix={arXiv},
      primaryClass={eess.SP},
      url={https://arxiv.org/abs/2603.06401}, 
}
```

Formal citation information will be updated after the paper metadata is finalized.

## License

* **Dataset:** CC BY 4.0
* **Code:** see the GitHub repository license
* **Pretrained models:** released together with this dataset repository unless otherwise specified

## Contact

**Xiaojie Li**
[xiaojieli@seu.edu.cn](mailto:xiaojieli@seu.edu.cn)
[xiaojieli@nuaa.edu.cn](mailto:xiaojieli@nuaa.edu.cn)