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<p>This paper addresses the challenges of security and reliability in simultaneously transmitting and reflecting reconfigurable intelligence surface (STAR-RIS) assisted integrated sensing, communication, and computation over-the-air (ISCCO) system. We investigate the trade-offs between covert communication, covert sensing, and Over-the-Air Computation (AirComp) reliability in scenarios involving both communication and sensing wardens. Specifically, to meet covert performance and reliability requirements, we derive covert rates for communication, sensing, and air computing under the assumption of perfect channel state information (CSI) by the wardens. The radar sensing Cramér-Rao bound (CRB) and AirComp mean square error (MSE) are used to represent sensing and computing performance. Building on this, we propose an optimization framework to minimize the error probability of AirComp while satisfying the covert communication and covert sensing requirements as well as the radar sensing CRB constraints. To solve the inherently non-convex optimization problem, we propose a smoothed exact penalty algorithm with a twice continuously differentiable property. This approach involves the joint optimization of data transmission beam-forming, radar sensing beamforming, data aggregation beamforming, and the STAR-RIS matrix. The problem is reformulated into a difference of convex functions form to search for a local optimum. Simulations demonstrate that our algorithm surpasses benchmark schemes in convergence and robustness.</p>

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STAR-RIS enabled covert integration of sensing communication and over-the-air computing with analysis and optimization

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月30日

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  • Miao Zhang,
  • Chao Wang,
  • Tianyu Ren,
  • Jing Li

摘要

This paper addresses the challenges of security and reliability in simultaneously transmitting and reflecting reconfigurable intelligence surface (STAR-RIS) assisted integrated sensing, communication, and computation over-the-air (ISCCO) system. We investigate the trade-offs between covert communication, covert sensing, and Over-the-Air Computation (AirComp) reliability in scenarios involving both communication and sensing wardens. Specifically, to meet covert performance and reliability requirements, we derive covert rates for communication, sensing, and air computing under the assumption of perfect channel state information (CSI) by the wardens. The radar sensing Cramér-Rao bound (CRB) and AirComp mean square error (MSE) are used to represent sensing and computing performance. Building on this, we propose an optimization framework to minimize the error probability of AirComp while satisfying the covert communication and covert sensing requirements as well as the radar sensing CRB constraints. To solve the inherently non-convex optimization problem, we propose a smoothed exact penalty algorithm with a twice continuously differentiable property. This approach involves the joint optimization of data transmission beam-forming, radar sensing beamforming, data aggregation beamforming, and the STAR-RIS matrix. The problem is reformulated into a difference of convex functions form to search for a local optimum. Simulations demonstrate that our algorithm surpasses benchmark schemes in convergence and robustness.