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Open Access

AI-Enabled STAR-RIS Aided MISO ISAC Secure Communications

School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China, and is also with National Mobile Communications Research Laboratory, Southeast University, Nanjing 210019, China
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
School of Computing and Digital Technology, Birmingham City University, Birmingham B55JU, UK
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Abstract

A simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided integrated sensing and communication (ISAC) dual-secure communication system is studied in this paper. The sensed target and legitimate users (LUs) are situated on the opposite sides of the STAR-RIS, and the energy splitting and time switching protocols are applied in the STAR-RIS, respectively. The long-term average security rate for LUs is maximized by the joint design of the base station (BS) transmit beamforming and receive filter, along with the STAR-RIS transmitting and reflecting coefficients, under guarantying the echo signal-to-noise ratio thresholds and rate constraints for the LUs. Since the channel information changes over time, conventional convex optimization techniques cannot provide the optimal performance for the system, and result in excessively high computational complexity in the exploration of the long-term gains for the system. Taking continuity control decisions into account, the deep deterministic policy gradient and soft actor-critic algorithms based on off-policy are applied to address the complex non-convex problem. Simulation results comprehensively evaluate the performance of the proposed two reinforcement learning algorithms and demonstrate that STAR-RIS is remarkably better than the two benchmarks in the ISAC system.

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Tsinghua Science and Technology
Pages 998-1011
Cite this article:
Zhu Z, Gong M, Sun G, et al. AI-Enabled STAR-RIS Aided MISO ISAC Secure Communications. Tsinghua Science and Technology, 2025, 30(3): 998-1011. https://doi.org/10.26599/TST.2024.9010086

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Received: 01 December 2023
Revised: 13 February 2024
Accepted: 08 May 2024
Published: 30 December 2024
© The Author(s) 2025.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

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