User Localization and Environment Mapping With the Assistance of RIS

With the introduction of sixth-generation (6 G) communication, the attention to integrated sensing and communication (ISAC) is growing rapidly due to the diverse requirements for 6 G communication services. However, the sensing performance in wireless scenarios is constrained by limited resources, such as the number of array antennas, spectrum, and power. Nevertheless, reconfigurable intelligent surface (RIS) is suitable for assisting ISAC because it can manipulate the incident signals with relatively lower power consumption. Therefore, this paper proposes a user localization and environment estimation problem with the assistance of orthogonal frequency-division multiplexing (OFDM) and RIS. Considering that carrier frequency offsets (CFO) will impact the location estimation in OFDM, we first investigate the joint estimation of time of arrivals (TOA) and 2-D direction of arrivals (DOA) without CFO estimation by taking advantage of matrix transformation. In order to increase the ability of environment estimation of wireless signals, we develop an efficient environment estimation method with the help of RIS to adjust the directions of the incident signals in different frequencies. Finally, by taking the space-time continuity of user movement and the geometry features of environment into account, we establish the probability transition model of the estimation process for user's location and environment by factor graph. The performance of our factor graph-based estimation algorithm is demonstrated by simulation results.