| | --- |
| | 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 |
| |
|
| | ## 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 |
| |
|
| | ## 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) |
