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A fundamental challenge in millimeter-wave (mmWave) communication is thesusceptibility to blocking objects. One way to alleviate this problem is theuse of reconfigurable intelligent surfaces (RIS). Nevertheless, due to thelarge number of passive reflecting elements on RIS, channel estimation turnsout to be a challenging task. In this paper, we address the channel estimationfor RIS-aided mmWave communication systems based on a localization method. Theproposed idea consists of exploiting the sparsity of the mmWave channel and thetopology of the RIS. In particular, we first propose the concept of reflectingunit set (RUS) to improve the flexibility of RIS. We then propose a novelcoplanar maximum likelihood-based (CML) 3D positioning method based on the RUS,and derive the Cramer-Rao lower bound (CRLB) for the positioning method.Furthermore, we develop an efficient positioning-based channel estimationscheme with low computational complexity. Compared to state-of-the-art methods,our proposed method requires less time-frequency resources in channelacquisition as the complexity is independent to the total size of the RIS butdepends on the size of the RUSs, which is only a small portion of the RIS.Large performance gains are confirmed in simulations, which proves theeffectiveness of the proposed method.

A 3D Positioning-based Channel Estimation Method for RIS-aided mmWave Communications