Nested Tensor-Based Framework for ISAC Assisted by Reconfigurable Intelligent Surface

In this paper, we propose a nested tensor-based framework for integrated near-field sensing and far-field communication assisted by reconfigurable intelligent surface (RIS). With the multi-dimensional resources of the considered integrated sensing and communication (ISAC) scenario and the Khatri-Rao space-time (KRST) coding, we formulate the received ISAC signal as a fourth-order nested tensor. By utilizing the algebraic structure of the nested tensor, a nested tensor-based joint sensing and communication scheme is designed to realize symbol detection and target localization without sending the specialized pilots. Moreover, the detection and localization accuracy is further improved by combining the dimensions of sensing and communication signals. Simulation results show that the proposed scheme provides superior ISAC performance with low complexity, which confirms the potential advantage of nested tensor-based framework in RIS-assisted ISAC systems.