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This paper investigates the performance of reconfigurable intelligent surface(RIS)-aided massive multiple-input multiple-output (MIMO) systems with directlinks, and the phase shifts of the RIS are designed based on the statisticalchannel state information (CSI). We first derive the closed-form expression ofthe uplink ergodic data rate. Then, based on the derived expression, we use thegenetic algorithm (GA) to solve the sum data rate maximization problem. Withlow-complexity maximal-ratio combination (MRC) and low-overhead statisticalCSI-based scheme, we validate that the RIS can still bring significantperformance gains to traditional massive MIMO systems.

Statistical CSI-based Design for Reconfigurable Intelligent Surface-aided Massive MIMO Systems with Direct Links