---
license: cdla-permissive-2.0
pretty_name: mu_mimo
size_categories:
- 100K<n<1M
---

# MU-MIMO datasets

This is the official repository of MU-MIMO datasets used in "SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing" (ICDCS 2023).

`*-h_mat.npy` and `*-v_mat.npy` are input samples and targets, respectively.

If you have any questions about the datasets, please directly contact [`Niloofar Bahadori`](https://niloobahadori.github.io/) as she built both the real and synthetic datasets.

The code is available [here](https://github.com/yoshitomo-matsubara/split-beam).

## Citation

```bibtex
@inproceedings{bahadori2023splitbeam,
  title={{SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing}},
  author={Bahadori, Niloofar and Matsubara, Yoshitomo and Levorato, Marco and Restuccia, Francesco},
  booktitle={2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)},
  pages={864--874},
  year={2023},
  organization={IEEE}
}
```