Sum Rate and Cramér-Rao Lower Bound Analysis for RIS-Assisted Multiuser Large-Antenna ISAC

In integrated sensing and communication (ISAC) systems, reconfigurable intelligent surface (RIS) is often able to provide a virtual line-of-sight path to overcome blockage and introduce new degrees of freedom to enhance both communications and sensing performances. In this paper, we explore the synergistic integration of massive multiple-input-multiple-output (MIMO) ISAC and RIS technologies. We first consider the uplink training phase and estimate the channels between the base station and communication users, by using the minimum mean square error method. Then, we derive the closed-form expressions for the downlink communications rate and the Cramér-Rao lower bound for the estimation of the azimuth and elevation angles associated with the sensing target. Extensive simulations verify that the derived analytical results match well with Monte Carlo simulation results. Furthermore, communication and sensing performances are significantly improved owing to the deployment of the RIS. Our analysis lay an important foundation for optimizing RIS-assisted ISAC systems.