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High-Resolution Channel Estimation for Intelligent Reflecting Surface-Assisted MmWave Communications

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Document pages: 6 pages

Abstract: In this paper, we study the high-resolution channel estimation problem forintelligent reflecting surface (IRS)-assisted millimeter wave (mmWave)multiple-input-multiple-output (MIMO) communications, which is a prerequisiteto guarantee further high-rate data transmission. Considering the typicalsparsity of mmWave channels, we formulate the cascaded channel estimationproblem from a sparse signal recovery perspective, and then propose a noveltwo-step cascaded channel estimation protocol to estimate the cascadeduser-IRS-base station channel with high-resolution for IRS-assisted mmWave MIMOcommunications. More specifically, the first step is to estimate the coarseangular domain information (ADI) and further establish the robust uplink bybeam training. In the second step, by exploiting the coarse ADI, an adaptivegrid matching pursuit (AGMP) algorithm is proposed to estimate thehigh-resolution cascaded channel state information (CSI) with low complexity.Simulation results verify that the proposed two-step channel estimationprotocol significantly outperforms the state-of-the-art scheme, i.e., beamtraining based channel estimation, and meanwhile can reap near-optimal systemperformance achieved by perfect CSI.

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