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Experimental setup

Experimental setup

Authors and citation

If you find this repository helpful, please cite our work:

  • [ISCAS 2024] OpenDPD: An Open-Source End-to-End Learning & Benchmarking Framework for Wideband Power Amplifier Modeling and Digital Pre-Distortion

    @INPROCEEDINGS{Wu2024ISCAS,
      author={Wu, Yizhuo and Singh, Gagan Deep and Beikmirza, Mohammadreza and de Vreede, Leo C. N. and Alavi, Morteza and Gao, Chang},
      booktitle={2024 IEEE International Symposium on Circuits and Systems (ISCAS)}, 
      title={OpenDPD: An Open-Source End-to-End Learning & Benchmarking Framework for Wideband Power Amplifier Modeling and Digital Pre-Distortion}, 
      year={2024},
      volume={},
      number={},
      pages={1-5},
      keywords={Codes;Transmitters;OFDM;Power amplifiers;Artificial neural networks;Documentation;Benchmark testing;digital pre-distortion;behavioral modeling;deep neural network;power amplifier;digital transmitter},
      doi={10.1109/ISCAS58744.2024.10558162}}
    

  • [IMS/MWTL 2024] MP-DPD: Low-Complexity Mixed-Precision Neural Networks for Energy-Efficient Digital Pre-distortion of Wideband Power Amplifiers

    @ARTICLE{Wu2024IMS,
      author={Wu, Yizhuo and Li, Ang and Beikmirza, Mohammadreza and Singh, Gagan Deep and Chen, Qinyu and de Vreede, Leo C. N. and Alavi, Morteza and Gao, Chang},
      journal={IEEE Microwave and Wireless Technology Letters}, 
      title={MP-DPD: Low-Complexity Mixed-Precision Neural Networks for Energy-Efficient Digital Predistortion of Wideband Power Amplifiers}, 
      year={2024},
      volume={},
      number={},
      pages={1-4},
      keywords={Deep neural network (DNN);digital predistortion (DPD);digital transmitter (DTX);power amplifier (PA);quantization},
      doi={10.1109/LMWT.2024.3386330}}
    

  • [IMS/MWTL 2025] DeltaDPD: Exploiting Dynamic Temporal Sparsity in Recurrent Neural Networks for Energy-Efficient Wideband Digital Predistortion

    @article{Wu2025MWTL,
       title={DeltaDPD: Exploiting Dynamic Temporal Sparsity in Recurrent Neural Networks for Energy-Efficient Wideband Digital Predistortion},
       ISSN={2771-957X},
       url={http://dx.doi.org/10.1109/LMWT.2025.3565004},
       DOI={10.1109/lmwt.2025.3565004},
       journal={IEEE Microwave and Wireless Technology Letters},
       publisher={Institute of Electrical and Electronics Engineers (IEEE)},
       author={Wu, Yizhuo and Zhu, Yi and Qian, Kun and Chen, Qinyu and Zhu, Anding and Gajadharsing, John and de Vreede, Leo C. N. and Gao, Chang},
       year={2025},
       pages={1–4} }
    

Contributors

  • Chang Gao - Project Lead
  • Yizhuo Wu - Core Developer
  • Ang Li - Core Developer
  • Huanqiang Duan - Contributor
  • Ruishen Yang - Contributor
  • Qian Wu (qian.wu@ucdconnect.ie) - Contributor