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Reconfigurable intelligent surface (RIS) has emerged as a cost-effectivesolution to improve wireless communication performance through just passivereflection. Recently, the concept of simultaneously transmitting and reflectingRIS (STAR-RIS) has appeared but the study of minimumsignal-to-interference-plus-noise ratio (SINR) and the impact of hardwareimpairments (HWIs) remain open. In addition to previous works on STAR-RIS, weconsider a massive multiple-input multiple-output (mMIMO) base station (BS)serving multiple user equipments (UEs) at both sides of the RIS. Specifically,in this work, focusing on the downlink of a single cell, we derive the minimumSINR obtained by the optimal linear precoder (OLP) with HWIs in closed form.The OLP maximises the minimum SINR subject to a given power constraint for anygiven passive beamforming matrix (PBM). Next, we obtain deterministicequivalents (DEs) for the OLP and the minimum SINR, which are then used tooptimise the PBM. Notably, based on the DEs and statistical channel stateinformation (CSI), we optimise simultaneously the amplitude and phase shift byusing a projected gradient ascent algorithm (PGAM) for both energy splitting(ES) and mode switching (MS) STAR-RIS operation protocols with reducedfeedback, \textcolor{black}{which is quite crucial for STAR-RIS systems thatinclude the double number or variables compared to reflecting only RIS.}Simulations verify the analytical results, shed light on the impact of HWIs,and demonstrate the better performance of STAR-RIS compared to conventionalRIS.

Max-Min SINR Analysis of STAR-RIS Assisted Massive MIMO Systems with Hardware Impairments