Data-Driven Deep Learning to Design Pilot and Channel Estimator for Massive MIMO

@article{Ma2020DataDrivenDL,
  title={Data-Driven Deep Learning to Design Pilot and Channel Estimator for Massive MIMO},
  author={X. Ma and Z. Gao},
  journal={IEEE Transactions on Vehicular Technology},
  year={2020},
  volume={69},
  pages={5677-5682}
}
  • X. Ma, Z. Gao
  • Published 2020
  • Computer Science, Engineering, Mathematics
  • IEEE Transactions on Vehicular Technology
In this paper, we propose a data-driven deep learning (DL) approach to jointly design the pilot signals and channel estimator for wideband massive multiple-input multiple-output (MIMO) systems. By exploiting the angular-domain compressibility of massive MIMO channels, the conceived DL framework can reliably reconstruct the high-dimensional channels from the under-determined measurements. Specifically, we design an end-to-end deep neural network (DNN) architecture composed of dimensionality… Expand
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