In this paper, we consider the channel estimation problem in an IRS-assisted wireless communication system where both the direct and reflected users can be served simultaneously. It is assumed that all the channels experience block fading where the reflecting channel variation follows a classical autoregressive (AR) model. In order to obtain accurate channel state information (CSI) of all the users, the channel estimation process is performed in two stages. In the first stage, we employ a classical least square (LS) method to estimate the direct channels. In the second stage, we can remove the signal interference of the direct users to the reflected users by performing the channel estimation in the null space of the direct channels. Then, we perform reflecting channel estimation by using the Kalman filter, which is able to track the channel variations by taking advantage of prior estimations. Numerical results demonstrate that the proposed approach outperforms the existing method in terms of channel estimation errors for both the direct and reflected users.


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    Title :

    Uplink Channel Estimation for Intelligent Reflecting Surface Aided Direct and Reflected Users


    Contributors:
    Du, Qianqian (author) / Dong, Zheng (author) / Xu, Hongji (author) / Wei, Ning (author) / Liu, Ju (author)


    Publication date :

    2022-06-01


    Size :

    789138 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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