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• W4290996974 abstract "This paper analyzes and optimizes the reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems with zero-forcing (ZF) detectors under imperfect channel state information (CSI). We first propose a low-overhead minimum mean square error (MMSE) channel estimator, and then derive and analyze closed-form expressions for the uplink achievable rate. Our analytical results prove that: 1) regardless of the RIS phase shift design, the rate of all users scales at least on the order of $mathcal{O}left( {{{log }_2}(MN)} right)$, where M and N are the numbers of antennas and reflecting elements, respectively; 2) by aligning the RIS phase shifts to one user, the rate of this user can at most scale on the order of $mathcal{O}left( {{{log }_2}(MN)} right)$. Furthermore, we propose a low-complexity majorization-minimization (MM)-based algorithm to optimize the sum user rate, where closed-form solutions are obtained in each iteration. Finally, simulation results validate all derived analytical results. Our simulation results also show that the maximum sum rate can be closely approached by simply aligning the RIS phase shifts to an arbitrary user." @default.
• W4290996974 created "2022-08-13" @default.
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• W4290996974 date "2022-05-16" @default.
• W4290996974 modified "2023-09-28" @default.
• W4290996974 title "Analysis and Optimization of RIS-Aided Massive MIMO with ZF Detectors and Imperfect CSI" @default.
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• W4290996974 doi "https://doi.org/10.1109/icc45855.2022.9838403" @default.
• W4290996974 hasPublicationYear "2022" @default.
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