Large-Scale Intelligent Surfaces Enabled Unified Near-Field and Far-Field Communications: Codebook Design and Beam Training

Benefiting from the large-scale antenna arrays, the forthcoming 6G networks are capable of providing high spectral efficiency by utilizing spatial diversity. The near-field region also expands with the large aperture, and thus, users may randomly distribute in both the near and far fields, leading to near-far (NF) field communications. In this article, by deploying large-scale reconfigurable intelligent surfaces (RISs) that serve as an energy-efficient solution, a general codebook-based beam training scheme for the RIS-aided NF-field communications is proposed, which does not rely on any channel state information. Starting from the basics of NF-field communications, we present the design principles and key technologies of the NF-field codebook-based beam training, targeting at serving users located either in the near field or the far field without prior knowledge of their locations. Utilizing the general scheme, a case study is presented for a large-scale RIS-enabled multiuser communication system. The proposed scheme is further extended to the wideband transmission, the omni-directional surface case, and the communication-assisting sensing. Future research directions for NF-field communications enabled by intelligent surfaces are also discussed.