Radio Tomographic Imaging With Reconfigurable Intelligent Surfaces

Radio tomographic imaging (RTI) is a device-free sensing technology that can image the radio frequency (RF) attenuation of physical objects in the environment. RTI uses received signal strength (RSS) information from a wireless communication network (WCN) to perform image reconstruction. However it requires a dense WCN consisting of a large number of nodes making it difficult to apply in realistic WCN. In this paper we investigate the performance of RTI when reconfigurable intelligent surfaces (RISs) are integrated into the WCN for integrated sensing and communication (ISAC). This approach can potentially enable the use of RTI in realistic WCN without a large number of nodes. Theoretical and numerical comparisons based on the Cramér-Rao Lower Bound (CRLB) are provided to verify the improvement on sensing performance brought by RIS. The scaling behavior of the reconstruction error as a function of the number of RIS element groups is also derived. Simulations are conducted to validate the proposed RIS-RTI system with a limited number of nodes. The results indicate that incorporating RIS can reduce the necessary number of nodes by more than a half while maintaining high-quality reconstruction compared to a network without RIS.