Detection of Visible Region in Ultra-Large-Scale RIS- Assisted mmWave Communication Systems

Ultra-large-scale (ULS) reconfigurable intelligent surfaces (RISs) are promising for mitigating channel blockage and improving coverage for millimeter-wave (mmWave) communications. In practice, the environmental obstacles and the near-field effect caused by RIS's vast scale may cause shadowing effect, necessitating the identification of visible regions (VRs) for precise channel estimation and user localization. In this paper, we investigate the VR detection issue for ULS RIS-assisted mmWave communication systems. By utilizing the block characteristic of VR, two efficient methods, namely binary search and block boundary detection, are proposed to precisely identify the VR of users with low complexity. Numerical results demonstrate that the binary search can significantly reduce the detection costs while ensuring comparable or even higher recovery accuracy. The block boundary method can further enhance the VR recovery accuracy under conditions of restricted transmitting power.