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Channel estimation is the main hurdle to reaping the benefits promised by theintelligent reflecting surface (IRS), due to its absence of ability totransmit/receive pilot signals as well as the huge number of channelcoefficients associated with its reflecting elements. Recently, a breakthroughwas made in reducing the channel estimation overhead by revealing that theIRS-BS (base station) channels are common in the cascaded user-IRS-BS channelsof all the users, and if the cascaded channel of one typical user is estimated,the other users' cascaded channels can be estimated very quickly based on theircorrelation with the typical user's channel \cite{b5}. One limitation of thisstrategy, however, is the waste of user energy, because many users need to keepsilent when the typical user's channel is estimated. In this paper, we revealanother correlation hidden in the cascaded user-IRS-BS channels by observingthat the user-IRS channel is common in all the cascaded channels from users toeach BS antenna as well. Building upon this finding, we propose a noveltwo-phase channel estimation protocol in the uplink communication.Specifically, in Phase I, the correlation coefficients between the channels ofa typical BS antenna and those of the other antennas are estimated; while inPhase II, the cascaded channel of the typical antenna is estimated. Inparticular, all the users can transmit throughput Phase I and Phase II. Underthis strategy, it is theoretically shown that the minimum number of timeinstants required for perfect channel estimation is the same as that of theaforementioned strategy in the ideal case without BS noise. Then, in the casewith BS noise, we show by simulation that the channel estimation error of ourproposed scheme is significantly reduced thanks to the full exploitation of theuser energy.

A New Channel Estimation Strategy in Intelligent Reflecting Surface Assisted Networks