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Due to the passive nature of Intelligent Reflecting Surface (IRS), channelestimation is a fundamental challenge in IRS-aided wireless networks.Particularly, as the number of IRS reflecting elements and/or that ofIRS-served users increase, the channel training overhead becomes excessivelyhigh. To tackle this challenge, we propose in this paper a new anchor-assistedtwo-phase channel estimation scheme, where two anchor nodes, namely A1 and A2,are deployed near the IRS for helping the base station (BS) to acquire thecascaded BS-IRS-user channels. Specifically, in the first phase, the partialchannel state information (CSI), i.e., the element-wise channel gain square, ofthe BS-IRS link is obtained by estimating the BS-IRS-A1/A2 channels and theA1-IRS-A2 channel, separately. Then, in the second phase, by leveraging suchpartial knowledge of the BS-IRS channel that is common to all users, theindividual cascaded BS-IRS-user channels are efficiently estimated. Simulationresults demonstrate that the proposed anchor-assisted channel estimation schemeis able to achieve comparable mean-squared error (MSE) performance as comparedto the conventional scheme, but with significantly reduced channel trainingtime.

Anchor-Assisted Intelligent Reflecting Surface Channel Estimation for Multiuser Communications