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Intelligent reflecting surface (IRS) has emerged as a promising paradigm toimprove the capacity and reliability of a wireless communication system bysmartly reconfiguring the wireless propagation environment. To achieve thepromising gains of IRS, the acquisition of the channel state information (CSI)is essential, which however is practically difficult since the IRS does notemploy any transmit/receive radio frequency (RF) chains in general and it haslimited signal processing capability. In this paper, we study the uplinkchannel estimation problem for an IRS-aided multiuser single-input multi-output(SIMO) system, and propose a novel two-phase channel estimation (2PCE) strategywhich can alleviate the negative effects caused by error propagation in theexisting three-phase channel estimation approach, i.e., the channel estimationerrors in previous phases will deteriorate the estimation performance in laterphases, and enhance the channel estimation performance with the same amount ofchannel training overhead as in the existing approach. Moreover, the asymptoticmean squared error (MSE) of the 2PCE strategy is analyzed when the least-square(LS) channel estimation method is employed, and we show that the 2PCE strategycan outperform the existing approach. Finally, extensive simulation results arepresented to validate the effectiveness of the 2PCE strategy.

Channel Estimation for IRS-aided Multiuser Communications with Reduced Error Propagation