This is the official repository of our paper "SplitBeam: Effective and Efficient Beamforming in Wi-Fi Networks Through Split Computing" presented at ICDCS 2023.
The datasets used in the paper are hosted at Hugging Face Datasets.
You can use the following commands to download the datasets:
mkdir -p ./resource/datasets/
git lfs install
git clone https://huggingface.co/datasets/yoshitomo-matsubara/mu-mimo ./resource/datasets/
If you have any questions regarding MATLAB and/or datasets, please directly contact
Niloofar Bahadori
as she provided MATLAB code and Python code to wrap
the MATLAB code, set up the MATLAB environment, and created the datasets.
- Python 3.8
- MATLAB 2021R
- conda
conda env create -f environment.yml
~/anaconda3/bin/pip3 install -r requirements.txt --user
Use scripts under scripts/
e.g.,
sh scripts/2x2-20mhz/env1-batch.sh
sh scripts/2x2-20mhz/env2-batch.sh
Use scripts under scripts-quantization/
e.g.,
sh scripts-quantization/2x2-20mhz/env1-batch.sh
sh scripts-quantization/2x2-20mhz/env2-batch.sh
@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}
}