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

2025-04-18

AI Summary

This paper addresses the joint optimization of covert transmission and channel tracking in RIS-empowered Integrated Sensing and Covert Communication (ISCC) systems, under air-based, non-cooperative, and mobile surveillance scenarios. We propose a robust sensing-communication co-design framework that jointly optimizes the communication beamformer, sensing signal covariance matrix, and RIS phase shifts to maximize the covert rate under channel estimation errors, subject to covertness, sensing accuracy, power, and unit-modulus RIS element constraints. Key contributions include: (i) the first tightly coupled sensing-beamforming design specifically for covert communication; (ii) breaking the strong coupling bottleneck between covertness and sensing performance under estimation uncertainty; and (iii) revealing the fundamental trade-off between covert rate and sensing accuracy in ISCC. The algorithm converges stably, achieving over 40% improvement in covert sum-rate and millimeter-level channel tracking accuracy, demonstrating RIS’s substantial capacity enhancement for covert communications.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Responsible Web: Measurement, analysis, and circumvention of Web censorship

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 (ISCC) 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 ISCC systems.

Problem

• Enhance covert communication by sensing and tracking the warden's channel
• Jointly design beamformers and RIS phase shifts for robust covert transmission
• Maximize covert sum rate while balancing communication and sensing trade-offs

Innovation

• Sensing-then-beamforming framework for RIS-ISCC systems
• Robust optimization with alternating optimization techniques
• RIS enhances covert transmission rate effectively