Robust Secure Beam-Scanning for Near-Field ISAC Enabled by Location Division Multiple Access

This paper investigates a secure beam-scanning framework for near-field integrated sensing and communication (ISAC) systems, driven by location division multiple access (LDMA). Specifically, an ISAC base station performs full-map robust beam-scanning within each transmission cycle, aiming to simultaneously detect potential eavesdroppers (Eves) and ensure secure communication for legitimate users (Bobs). Based on the Bobs’ channel state information (CSI) obtained at the cycle’s start and the estimated CSI of Eves sensed in the previous cycle, we formulate a robust optimization problem. This problem jointly optimizes the hybrid analog-digital precoding and time allocation for beam-scanning, with the objective of maximizing the worst-case average sum secrecy rate. To simplify the solution process, we first eliminate or relax the semi-infinite constraints caused by uncertain multipath channels from two perspectives: convex hull and bounded uncertainty. Subsequently, we design a near-field LDMA codebook in both azimuth and distance domains to construct ideal radar beampatterns for covering and partitioning the spatial scanning region. We also develop efficient analog precoders to significantly reduce computational complexity. Based on the convex hull model, we develop a low-complexity alternating optimization (AO) algorithm. In addition, for the bounded uncertainty model, we propose a semidefinite relaxation-based AO algorithm without requiring a rank-one constraint. Simulation results demonstrate that the proposed framework enables effective full-map Eves sensing while guaranteeing secure communication for Bobs. Moreover, the convex hull-based algorithm exhibits superior robustness and scalability compared to conventional bounded uncertainty approaches.