UWMMSE-stability

Tensorflow implementation of Stability Analysis of UWMMSE

Overview

This library contains a Tensorflow implementation of the paper Stability Analysis of Unfolded WMMSE for Power Allocation[1].

Dependencies

• python>=3.6
• tensorflow>=1.14.0: https://tensorflow.org
• numpy
• matplotlib

Structure

• main: Main code for generating dataset and training/evaluating UWMMSE model. Run as python3 main.py [dataset ID] [exp ID] [mode]. Eg., to train UWMMSE on dataset with ID set3, run python3 main.py set3 uwmmse train. Generates dataset with given ID if not already present.
• validate: Plot figures 1(a) & 1(b) in the paper. Run as python3 main.py [dataset ID]. Eg., to run on dataset with ID set3, run python3 validate.py set3
• model: Defines the UWMMSE model.
• data: should contain your dataset in folder {dataset ID}.
• models: Stores trained models in a folder with same name as {datset ID}.
• results: Stores results in a folder with same name as {datset ID}.

Usage

Please cite [1] in your work when using this library in your experiments.

Feedback

For questions and comments, feel free to contact Arindam Chowdhury.

Citation

[1] Chowdhury A, Gama F, Segarra S. Stability Analysis of Unfolded WMMSE for Power Allocation. 
arXiv preprint arXiv:2110.07471 2021 Oct 14.

BibTeX format:

@article{chowdhury2021stability,
  title={Stability Analysis of Unfolded WMMSE for Power Allocation},
  author={Chowdhury, Arindam and Gama, Fernando and Segarra, Santiago},
  journal={arXiv e-prints},
  pages={arXiv--2110},
  year={2021}
}