RIS-Assisted Multi-User Localization in UAV-Enabled mmWave Wireless Networks

Abstract

Localization techniques based on time of arrival (TOA) and angle of arrival (AOA) have been widely used in mobile communication systems and the localization accuracy can suffer from severe path loss and blockage. The mobility of UAVs and the signal redirection capabilities of reconfigurable intelligent surfaces (RISs) can be utilized to reduce these negative effects. In this paper, we propose a multi-user localization scheme in UAV-enabled millimeter-wave wireless networks, where the UAV localizes the chosen ground user by receiving the positioning reference signal from both the direct path and the reflected path via a RIS in each time instance. We derive the positioning error bound (PEB) based on the Fisher information matrix (FIM) of the unknown channel parameters and location parameters. Then we propose an alternating algorithm to minimize the maximum PEB among all users, by optimizing the UAV trajectory, the user scheduling, the UAV beamforming, and the RIS phase shifts iteratively until convergence. Furthermore, we formulate a robust optimization problem with imperfect knowledge of location parameters to minimize the maximum worst-case PEB, which can also be solved by the alternating algorithm. Numerical results show that the proposed alternating algorithm can improve the localization accuracy by more than twice compared to the scheme with a fixed base station and the scheme without RIS deployment.