Analysis and Optimization of Spatially-Correlated RIS-Aided Secure Massive MIMO Systems With Low-Resolution DACs

We investigate the downlink secrecy performance of reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) systems in the presence of a multi-antenna eavesdropper. We first derive a tight closed-form expression for characterizing the lower bound of the achievable ergodic secrecy rate under spatially correlated channels, taking into account low-resolution digital-to-analog converters (DACs) and RIS phase noise. Subsequently, building upon the derived results, we optimize the power allocation among the information signal and artificial noise in closed form and the RIS phase shifts by developing a projected gradient ascent algorithm, which requires only statistical channel state information of the aggregated channel with low implementational complexity. All theoretical analyses and the effectiveness of the proposed algorithm are corroborated by simulation experiments. Our results reveal that low-resolution DAC can be beneficial with equal power allocation when the number of RIS elements is small. Besides, the detrimental influence attributed to low-resolution DACs gains prominence as the number of RIS elements grows substantially.