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Sensing-Then-Beamforming: Robust Transmission Design for RIS-Empowered Integrated Sensing and Covert Communication

Xingyu Zhao, Min Li, Ming-Min Zhao, Shihao Yan, Min-Jian Zhao

TL;DR

This paper tackles robust covert communication in RIS-empowered ISAC systems by introducing a sensing-then-beamforming framework. The transmitter (Alice) uses EKF-based sensing to actively track a mobile warden Willie and construct refined CSI for both Alice-Willie and RIS-Willie links, enabling a robust joint design of communications, sensing, and RIS phase shifts. An alternating optimization scheme integrates SCA, the S-procedure, semidefinite relaxation, and sequential rank-one constraint relaxation to solve a non-convex, CSI-uncertainty-aware problem aiming to maximize covert sum rate under covert, sensing, power, and unit-modulus constraints. Simulations show that RIS significantly boosts covert rates, and the proposed scheme tracks Willie effectively while preserving covertness, revealing a fundamental trade-off between sensing accuracy and communication performance. The results highlight practical benefits for RIS-enabled ISACC in scenarios with aerial wardens and provide a foundation for extensions to multi-warden and advanced RIS technologies.

Abstract

Traditional covert communication often relies on the knowledge of the warden's channel state information, which is inherently challenging to obtain due to the non-cooperative nature and potential mobility of the warden. The integration of sensing and communication technology provides a promising solution by enabling the legitimate transmitter to sense and track the warden, thereby enhancing transmission covertness. In this paper, we develop a framework for sensing-then-beamforming in reconfigurable intelligent surface (RIS)-empowered integrated sensing and covert communication (ISACC) systems, where the transmitter (Alice) estimates and tracks the mobile aerial warden's channel using sensing echo signals while simultaneously sending covert information to multiple legitimate users (Bobs) with the assistance of RIS, under the surveillance of the warden (Willie). Considering channel estimation errors, we formulate a robust non-convex optimization problem that jointly designs the communication beamformers, the sensing signal covariance matrix at Alice, and the phase shifts at the RIS to maximize the covert sum rate of Bobs while satisfying the constraints related to covert communication, sensing, transmitter power, and the unit modulus of the RIS elements. To solve this complex problem, we develop an efficient algorithm using alternating optimization, successive convex approximation, S-procedure, sequential rank-one constraint relaxation, and semidefinite relaxation techniques. Numerical results confirm the convergence of the proposed algorithm and demonstrate its effectiveness in tracking the warden's channel while ensuring robust covert transmission. Furthermore, the results highlight the advantages of using RIS to enhance the covert transmission rate compared to baseline schemes, and also illustrate the intricate trade-off between communication and sensing in ISACC systems.

Sensing-Then-Beamforming: Robust Transmission Design for RIS-Empowered Integrated Sensing and Covert Communication

TL;DR

This paper tackles robust covert communication in RIS-empowered ISAC systems by introducing a sensing-then-beamforming framework. The transmitter (Alice) uses EKF-based sensing to actively track a mobile warden Willie and construct refined CSI for both Alice-Willie and RIS-Willie links, enabling a robust joint design of communications, sensing, and RIS phase shifts. An alternating optimization scheme integrates SCA, the S-procedure, semidefinite relaxation, and sequential rank-one constraint relaxation to solve a non-convex, CSI-uncertainty-aware problem aiming to maximize covert sum rate under covert, sensing, power, and unit-modulus constraints. Simulations show that RIS significantly boosts covert rates, and the proposed scheme tracks Willie effectively while preserving covertness, revealing a fundamental trade-off between sensing accuracy and communication performance. The results highlight practical benefits for RIS-enabled ISACC in scenarios with aerial wardens and provide a foundation for extensions to multi-warden and advanced RIS technologies.

Abstract

Traditional covert communication often relies on the knowledge of the warden's channel state information, which is inherently challenging to obtain due to the non-cooperative nature and potential mobility of the warden. The integration of sensing and communication technology provides a promising solution by enabling the legitimate transmitter to sense and track the warden, thereby enhancing transmission covertness. In this paper, we develop a framework for sensing-then-beamforming in reconfigurable intelligent surface (RIS)-empowered integrated sensing and covert communication (ISACC) systems, where the transmitter (Alice) estimates and tracks the mobile aerial warden's channel using sensing echo signals while simultaneously sending covert information to multiple legitimate users (Bobs) with the assistance of RIS, under the surveillance of the warden (Willie). Considering channel estimation errors, we formulate a robust non-convex optimization problem that jointly designs the communication beamformers, the sensing signal covariance matrix at Alice, and the phase shifts at the RIS to maximize the covert sum rate of Bobs while satisfying the constraints related to covert communication, sensing, transmitter power, and the unit modulus of the RIS elements. To solve this complex problem, we develop an efficient algorithm using alternating optimization, successive convex approximation, S-procedure, sequential rank-one constraint relaxation, and semidefinite relaxation techniques. Numerical results confirm the convergence of the proposed algorithm and demonstrate its effectiveness in tracking the warden's channel while ensuring robust covert transmission. Furthermore, the results highlight the advantages of using RIS to enhance the covert transmission rate compared to baseline schemes, and also illustrate the intricate trade-off between communication and sensing in ISACC systems.

Paper Structure

This paper contains 27 sections, 5 theorems, 64 equations, 12 figures, 3 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Signal Model
  4. Communication Signal
  5. Sensing Signal
  6. Tracking Model
  7. State evolution model of Willie
  8. Measurement model of Willie
  9. EKF process
  10. Performance Metrics
  11. Communication
  12. Sensing
  13. Covertness
  14. Robust Transmission Design based on the Sensing-Then-Beamforming Framework
  15. Transmission Protocol
  16. ...and 12 more sections

Key Result

Proposition 1

Considering the channel estimation errors in channel-willie, the covertness constraint in $\mathrm{C}2$ can be equivalently transformed into where $\mathbf{R}=\mathbf{W}_{\mathrm{c}} \mathbf{W}_{\mathrm{c}}^H-(\eta_2-1) \mathbf{R}_{\mathrm{s}}=\sum_{k \in \mathcal{K}} \mathbf{W}_k-(\eta_2-1) \mathbf{R}_{\mathrm{s}}$, and $\eta_2 \geq1$ is the solution to the equation $\ln x+\frac{1}{x}-1-\frac{2

Figures (12)

  • Figure 1: Illustration of the RIS-empowered ISACC system.
  • Figure 2: Diagram of the transmission protocol of RIS-empowered ISACC systems.
  • Figure 3: An example of our simulation scenario.
  • Figure 4: Convergence properties of Algorithm \ref{['alg:1']} with $N_\mathrm{A}=N_\mathrm{R}=10$ and $\mathrm{MSE}_{\max }=7$.
  • Figure 5: Average covert sum rate of Bobs versus the maximum transmit power with $N_\mathrm{A}=N_\mathrm{R}=10$ and $\mathrm{MSE}_{\max }=7$.
  • ...and 7 more figures

Theorems & Definitions (5)

  • Proposition 1
  • Lemma 1
  • Proposition 2
  • Proposition 3
  • Proposition 4