Is Channel Estimation Necessary to Select Phase-Shifts for RIS-Assisted Massive MIMO?

@article{Demir2022IsCE,
  title={Is Channel Estimation Necessary to Select Phase-Shifts for RIS-Assisted Massive MIMO?},
  author={Ozlem Tugfe Demir and Emil Bj{\"o}rnson},
  journal={ArXiv},
  year={2022},
  volume={abs/2106.09770}
}
Reconfigurable intelligent surfaces (RISs) have attracted great attention as a potential beyond 5G technology. These surfaces consist of many passive elements of metamaterials whose impedance can be controllable to change the characteristics of wireless signals impinging on them. Channel estimation is a critical task when it comes to the control of a large RIS when having a channel with a large number of multipath components. In this paper, we propose novel channel estimation schemes for… 
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TLDR
A learning-based method is proposed that trains a neural network to learn a mapping between the received downlink signal and the effective channel gains and outperforms the state-of-the-art methods.
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TLDR
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Novel channel estimation schemes that exploit the array geometry to identify a subspace of reduced rank that covers the eigenspace of any spatial correlation matrix are proposed.
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TLDR
Numerical results reveal the effectiveness of the proposed joint optimization problem, under different AP selection strategies, and the natural suitability of CF-mMIMO in supporting computation-of-oading applications with benefits over users’ transmit power and energy consumption, the offloading latency experienced, andThe total amount of allocated remote computational resources.

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