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+ pretty_name: mu_mimo
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+ size_categories:
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+ - 100K<n<1M
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+ # MU-MIMO datasets
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+ 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).
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+ `*-h_mat.npy` and `*-v_mat.npy` are input samples and targets, respectively.
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+ 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.
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+ The code is available [here](https://github.com/yoshitomo-matsubara/split-beam).
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+ ## Citation
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+ ```bibtex
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+ @inproceedings{bahadori2023splitbeam,
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+ title={{SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing}},
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+ author={Bahadori, Niloofar and Matsubara, Yoshitomo and Levorato, Marco and Restuccia, Francesco},
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+ booktitle={2023 IEEE 43rd International Conference on Distributed Computing Systems (ICDCS)},
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+ pages={864--874},
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+ year={2023},
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+ organization={IEEE}
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+ }
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+ ```