SIM辅助集成感知与隐蔽通信的鲁棒收发机设计

中文摘要 AI 辅助

堆叠智能超表面（SIM）已成为第六代集成感知与通信网络中一种有前景的波域处理技术，可减少对复杂射频硬件的依赖。然而，不完美的信道状态信息（CSI）可能损害感知性能和通信可靠性。此外，确保隐蔽传输带来了进一步的挑战，因为系统必须在感知潜在目标的同时，向未授权的监视者隐藏通信活动。这些挑战促使了鲁棒SIM辅助集成感知与隐蔽通信（ISACC）系统的发展。本文研究了不完美CSI下多用户、多目标ISACC系统的鲁棒收发机设计。我们联合优化发射和接收波束成形器、感知协方差矩阵和SIM相移，以最大化最坏情况下的最小感知信干噪比。该公式对信道不确定性有界、用户服务质量要求、发射功率预算、SIM相移和目标检测概率施加了约束。由于所提出的问题高度非凸，我们开发了一种基于S过程、连续凸逼近和半定松弛的交替优化框架。此外，为降低计算复杂度，我们推导了发射/接收波束成形器设计中涉及的鲁棒感知线性矩阵不等式（LMI）的精确低维表示。我们进一步开发了一种低复杂度的相位更新方法，避免了大型感知LMI。数值结果表明，所提出的设计优于随机相移和全数字波束成形基准，而低复杂度方案在显著降低计算成本的情况下实现了与基于LMI的方案相当的性能。

英文摘要

Stacked intelligent metasurfaces (SIMs) have emerged as a promising wave-domain processing technology for sixth-generation integrated sensing and communication networks, reducing reliance on complex radio-frequency hardware. Nevertheless, imperfect channel state information (CSI) can compromise sensing performance and communication reliability. Moreover, ensuring covert transmission introduces a further challenge, as the system must sense potential targets while concealing communication activity from unauthorized wardens. These challenges motivate the development of robust SIM-assisted integrated sensing and covert communication (ISACC) systems. In this paper, we investigate the robust transceiver design of a multi-user, multi-target ISACC system under imperfect CSI. We jointly optimize the transmit and receive beamformers, sensing covariance matrix, and SIM phase shifts to maximize the worst-case minimum sensing signal-to-interference-plus-noise ratio. The formulation enforces constraints on bounded channel uncertainties, user quality-of-service requirements, transmit-power budget, SIM phase shifts, and target detection probabilities. Since the formulated problem is highly non-convex, we develop an alternating optimization framework based on the S-procedure, successive convex approximation, and semidefinite relaxation. Furthermore, to reduce computational complexity, we derive exact lower-dimensional representations of the robust sensing linear matrix inequalities (LMIs) involved in transmit/receive-beamformer designs. We further develop a low-complexity phase-update method that avoids the large sensing LMIs. Numerical results demonstrate that the proposed design outperforms random phase shift and fully digital-beamforming benchmarks, while the low-complexity scheme achieves comparable performance to the LMI-based scheme at substantially lower computational cost.

发表机构

• King Fahd University of Petroleum and Minerals（法赫德国王石油与矿物大学）
• Fujairah University（富查伊拉大学）
• Menoufia University（门努菲亚大学）

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