ISAC-OTFS Enabled Secure Transmission Against Co-Existing Internal and External Eavesdroppers in Vehicular Networks
Zian Chen, Qian Xu, Zhaolin Zhang, Jiansong Huang, Wen–Bin Sun, Ling Wang · 2025
This paper proposes an integrated sensing and communication (ISAC)-enabled secure transmission scheme based on orthogonal time frequency space (OTFS) modulation and spatially selective artificial noise (AN) design, to counter passive interception from other regular users and unconnected external nodes in the vehicular networks. In the proposed scheme, we build the eavesdropping model for the ISAC-OTFS framework, then formulate a non-convex optimization problem to maximize the secrecy rate (SR) for the designated user. Firstly, through the radar sensing echoes, some critical parameters of the vehicles can be obtained by the designed maximum likelihood (ML) estimator. Subsequently, the estimation values of the required parameters are substituted into the objective function, thereby enabling the tractable solution of the formulated problem. Thirdly, the original problem is convexified via the semidefinite relaxation (SDR) and Charnes-Cooper transformation (CCT), and then the numerical solutions can be obtained through standard convex optimization techniques. Simulation results demonstrate the enhanced physical layer security (PLS) performance of the proposed scheme against the co-existing internal and external eavesdropping threats.