Corpus ID: 233423192

Adaptive Channel Estimation Based on Model-Driven Deep Learning for Wideband mmWave Systems

@inproceedings{Jin2021AdaptiveCE,
  title={Adaptive Channel Estimation Based on Model-Driven Deep Learning for Wideband mmWave Systems},
  author={Weijie Jin and Hengtao He and Chao-Kai Wen and Shi Jin and Geoffrey Y. Li},
  year={2021}
}
Channel estimation in wideband millimeter-wave (mmWave) systems is very challenging due to the beam squint effect. To solve the problem, we propose a learnable iterative shrinkage thresholding algorithm-based channel estimator (LISTA-CE) based on deep learning. The proposed channel estimator can learn to transform the beam-frequency mmWave channel into the domain with sparse features through training data. The transform domain enables us to adopt a simple denoiser with few trainable parameters… Expand

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