• Corpus ID: 239015863

Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systems

@article{Zhang2021DeepLP,
  title={Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systems},
  author={Yongshun Zhang and Jiayi Zhang and Yu Jin and Stefano Buzzi and Bo Ai},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.09001}
}
In this paper, a general framework for deep learning-based power control methods for max-min, max-product and max-sum-rate optimization in uplink cell-free massive multiple-input multiple-output (CF mMIMO) systems is proposed. Instead of using supervised learning, the proposed method relies on unsupervised learning, in which optimal power allocations are not required to be known, and thus has low training complexity. More specifically, a deep neural network (DNN) is trained to learn the map… 

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References

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TLDR
A deep learning (DL) based power control algorithm that solves the max-min user fairness problem in a cell-free massive multiple-input multiple-output (MIMO) system is proposed, which achieves a performance-complexity trade-off with around 400 times faster implementation and comparable performance to the optimization-based algorithm.
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