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The official source codes for "FedPDA: Collaborative Learning to Reduce Online-Adaptation Frequency of Neural Receivers"

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FedPDA

The official source codes for "FedPDA: Collaborative Learning to Reduce Online-Adaptation Frequency of Neural Receivers".

Prepare the Runtime Environment

To execute the code, a server equipped with at least one functional GPU is required to run TensorFlow version 2.11.1. Additionally, Sionna version 0.14.0 is necessary. To enable the sharpfed package in our codes, both joblib and paramiko are required.

License and Citation

FedPDA is Apache-2.0 licensed, as found in the LICENSE file. If you use our codes in your papers or projects, please cite it as:

@INPROCEEDINGS{6567033,
  author={Shuo Wang, Tianxin Wang, and Xudong Wang},
  booktitle={2025 Proceedings IEEE INFOCOM}, 
  title={FedPDA: Collaborative Learning to Reduce Online-Adaptation Frequency of Neural Receivers}, 
  year={2025},
  volume={},
  number={},
  pages={}
}

Besides, you should cite the reference of the Sionna package as mentioned in Sionna: An Open-Source Library for Next-Generation Physical Layer Research, and the reference of the TensorFlow package.

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The official source codes for "FedPDA: Collaborative Learning to Reduce Online-Adaptation Frequency of Neural Receivers"

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