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Intelligent reflecting surface (IRS) can bring significant performanceenhancement for wireless communication systems by reconfiguring wirelesschannels via passive signal reflection. However, such performance improvementgenerally relies on the knowledge of channel state information (CSI) forIRS-associated links. Prior IRS channel estimation strategies mainly estimateIRS-cascaded channels based on the excessive pilot signals received at theusers/base station (BS) with time-varying IRS reflections, which, however, arenot compatible with the existing channel training/estimation protocol forcellular networks. To address this issue, we propose in this paper a newchannel estimation scheme for IRS-assisted communication systems based on thereceived signal power measured at the user, which is practically attainablewithout the need of changing the current protocol. Specifically, due to thelack of signal phase information in power measurements, the autocorrelationmatrix of the BS-IRS-user cascaded channel is estimated by solving equivalentmatrix-rank-minimization problems. Simulation results are provided to verifythe effectiveness of the proposed channel estimation algorithm as well as theIRS passive reflection design based on the estimated channel autocorrelationmatrix.

Channel Autocorrelation Estimation for IRS-Aided Wireless Communications Based on Power Measurements