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Channel acquisition is one of the main challenges for the deployment ofreconfigurable intelligent surface (RIS) aided communication systems. This isbecause an RIS has a large number of reflective elements, which are passivedevices with no active transmitting/receiving abilities. In this paper, westudy the channel estimation problem for the RIS aided multi-usermillimeter-wave (mmWave) multi-input multi-output (MIMO) system. Specifically,we propose a novel channel estimation protocol for the above system to estimatethe cascaded channels, which are the products of the channels from the basestation (BS) to the RIS and from the RIS to the users. Further, since thecascaded channels are typically sparse, this allows us to formulate the channelestimation problem as a sparse recovery problem using compressive sensing (CS)techniques, thereby allowing the channels to be estimated with less trainingoverhead. Moreover, the sparse channel matrices of the cascaded channels of allusers have a common block sparsity structure due to the common channel betweenthe BS and the RIS. To take advantage of the common sparsity pattern, wepropose a two-step multi-user joint channel estimation procedure. In the firststep, we make use of the common column-block sparsity and project the receivedsignals onto the common column subspace. In the second step, we make use of therow-block sparsity of the projected signals and propose a multi-user jointsparse matrix recovery algorithm that takes into account the common channelbetween the BS and the RIS.

Channel Estimation for Reconfigurable Intelligent Surface Aided Multi-User mmWave MIMO Systems