Energy-Efficient Multiuser Localization in the RIS-Assisted IoT Networks

In various location-based Internet of Things (IoT) services, it is required to localize a large number of energy-limited devices simultaneously and accurately. In order to achieve this goal, a reconfigurable intelligent surface (RIS)-assisted positioning method for multiple IoT devices is proposed, where the signals transmitted by the users reach the base station (BS) along the direct path and the reflection path via the RIS. The difference in the propagation delay of the two paths is essential in the proposed triangulation-based localization framework, which is estimated via the cross-correlation function of the received signals. Based on the orthogonality of the transmitted signals, the optimization of the multiantenna BS and the RIS, with the goal of minimizing the total transmission power of the IoT devices, is constructed. For the orthogonal signal case, the nonconvex optimization problem for the RIS is recast into a convex problem via the semidefinite relaxation (SDR). For the nonorthogonal signal case, the zero-forcing (ZF) combining vectors at the BS are adopted to eliminate interferences among multiple users, and the block coordinate descent (BCD) algorithm is used to decouple the combining vectors and the RIS phases. Numerical results show that by using the proposed optimization method, decimeter-level positioning accuracy can be achieved with low-power consumption, and significant power gain can be achieved compared to the unoptimized RIS-assisted localization.