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Here is the introduction of the paper, Reconfigurable intelligent surface composed of a large number of passive components can significantly save hardware cost and energy. However, its channel estimation is challenging since RIS commonly operates as a passive reflecting device and cannot acquire the channel state information independently.
In this paper, a data-driven approach for achieving highly accurate channel estimation in RIS assisted multi-user system is proposed.
First, the channel estimation problem is modeled as a residual noise cancellation problem, and then the channel matrix with noise is obtained by a scaled least square (SLS) channel estimation. Finally, an enhanced deep residual shrinkage network (EDRSN) is designed to reduce the noise and further improve the accuracy of channel estimation. |
IEEE/ICACT20230157 Slide.03
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