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Dual-Functional Artificial Noise (DFAN) Aided Robust Covert Communications in Integrated Sensing and Communications

Runzhe Tang, Long Yang, Lv Lu, Zheng Zhang, Yuanwei Liu, Jian Chen

TL;DR

This work tackles covert communications in an integrated sensing and communications (ISAC) system by introducing dual-functional artificial noise (DFAN) with fluctuating power to simultaneously shelter covert transmissions and assist target sensing. It develops a robust design framework under imperfect and statistical Willie's CSI for infinite-blocklength operation, deriving closed-form minimum detection error probability (DEP) expressions and, in the statistical-WCSI case, the average DEP. A feasibility-checking difference-of-convex (DC) relaxation algorithm, leveraging the S-procedure and Bernstein-type inequality, is proposed to solve the non-convex beamforming and DFAN design problems while enforcing rank-one solutions. Simulation results demonstrate that DFAN substantially improves covert performance and sensing accuracy compared with benchmarks, and offer practical insights into WCSI robustness (especially under statistical WCSI) and design guidelines such as preferring DFAN over single-functional AN in ISAC covert settings. The study provides a scalable optimization framework with closed-form performance benchmarks that can guide secure ISAC deployments in radar-communication platforms.

Abstract

This paper investigates covert communications in an integrated sensing and communications system, where a dual-functional base station (called Alice) covertly transmits signals to a covert user (called Bob) while sensing multiple targets, with one of them acting as a potential watcher (called Willie) and maliciously eavesdropping on legitimate communications. To shelter the covert communications, Alice transmits additional dual-functional artificial noise (DFAN) with a varying power not only to create uncertainty at Willie's signal reception to confuse Willie but also to sense the targets simultaneously. Based on this framework, the weighted sum of the sensing beampattern means square error (MSE) and cross correlation is minimized by jointly optimizing the covert communication and DFAN signals subject to the minimum covert rate requirement. The robust design considers both cases of imperfect Willie's CSI (WCSI) and statistical WCSI. Under the worst-case assumption that Willie can adaptively adjust the detection threshold to achieve the best detection performance, the minimum detection error probability (DEP) at Willie is analytically derived in the closed-form expression. The formulated covertness constrained optimization problems are tackled by a feasibility-checking based difference-of-convex relaxation (DC) algorithm utilizing the S-procedure, Bernstein-type inequality, and the DC method. Simulation results validate the feasibility of the proposed scheme and demonstrate the covertness performance gains achieved by our proposed design over various benchmarks.

Dual-Functional Artificial Noise (DFAN) Aided Robust Covert Communications in Integrated Sensing and Communications

TL;DR

This work tackles covert communications in an integrated sensing and communications (ISAC) system by introducing dual-functional artificial noise (DFAN) with fluctuating power to simultaneously shelter covert transmissions and assist target sensing. It develops a robust design framework under imperfect and statistical Willie's CSI for infinite-blocklength operation, deriving closed-form minimum detection error probability (DEP) expressions and, in the statistical-WCSI case, the average DEP. A feasibility-checking difference-of-convex (DC) relaxation algorithm, leveraging the S-procedure and Bernstein-type inequality, is proposed to solve the non-convex beamforming and DFAN design problems while enforcing rank-one solutions. Simulation results demonstrate that DFAN substantially improves covert performance and sensing accuracy compared with benchmarks, and offer practical insights into WCSI robustness (especially under statistical WCSI) and design guidelines such as preferring DFAN over single-functional AN in ISAC covert settings. The study provides a scalable optimization framework with closed-form performance benchmarks that can guide secure ISAC deployments in radar-communication platforms.

Abstract

This paper investigates covert communications in an integrated sensing and communications system, where a dual-functional base station (called Alice) covertly transmits signals to a covert user (called Bob) while sensing multiple targets, with one of them acting as a potential watcher (called Willie) and maliciously eavesdropping on legitimate communications. To shelter the covert communications, Alice transmits additional dual-functional artificial noise (DFAN) with a varying power not only to create uncertainty at Willie's signal reception to confuse Willie but also to sense the targets simultaneously. Based on this framework, the weighted sum of the sensing beampattern means square error (MSE) and cross correlation is minimized by jointly optimizing the covert communication and DFAN signals subject to the minimum covert rate requirement. The robust design considers both cases of imperfect Willie's CSI (WCSI) and statistical WCSI. Under the worst-case assumption that Willie can adaptively adjust the detection threshold to achieve the best detection performance, the minimum detection error probability (DEP) at Willie is analytically derived in the closed-form expression. The formulated covertness constrained optimization problems are tackled by a feasibility-checking based difference-of-convex relaxation (DC) algorithm utilizing the S-procedure, Bernstein-type inequality, and the DC method. Simulation results validate the feasibility of the proposed scheme and demonstrate the covertness performance gains achieved by our proposed design over various benchmarks.
Paper Structure (16 sections, 2 theorems, 51 equations, 7 figures, 1 algorithm)

This paper contains 16 sections, 2 theorems, 51 equations, 7 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Contributions and Organization
  3. System Model
  4. Transmission Scheme
  5. Covert Communications
  6. Radar Sensing
  7. Covert Communications under Imperfect WCSI
  8. Covert Communications under Bounded WCSI Errors
  9. Covert Communications under Gaussian WCSI Errors
  10. Covert Communications under Statistical WCSI
  11. Covert Communications under statistical WCSI Errors
  12. Robust Beamforming Optimization Design under Statistical WCSI Errors
  13. Feasibility-Checking based DC Algorithm Design
  14. Simulation Results
  15. Discussions
  16. ...and 1 more sections

Key Result

Lemma 1

(S-procedure): Suppose that ${f_i}(\mathbf{x}) = {\mathbf{x}^H}{\mathbf{A}_i}\mathbf{x} + 2{\mathop{\rm Re}\nolimits} \{ \mathbf{b}_i^H\mathbf{x}\} + {c_i},i = 1,2,$ where ${\mathbf{x}}\in {{\mathbb{C}}^{N\times 1}}$, ${\mathbf{A}_i}\in {{\mathbb{C}}^{N\times N}}$, ${\mathbf{x}}\in {{\mathbb{C}}^{N

Figures (7)

  • Figure 1: Covert communications in an ISAC system.
  • Figure 2: Convergence of the proposed feasibility-checking based DC algorithm when $R_{\rm min}$ = 8 bps/Hz.
  • Figure 3: Covert rate versus $P_{\rm{b,max}}$ under bounded, Gaussian and statistical WCSI.
  • Figure 4: Covert rate versus $P_{\rm{A,max}}$ under statistical WCSI with $L(\eta_1,\mathbf{W}_1,\mathbf{T})\le 200$ and $P_{\rm{A,max}}=\frac{{x}}{{7}}10^{P_{\rm{t}}/10}\rm{ w}.$
  • Figure 5: Sensing beampattern error versus $R_{\rm min}$ with $P_{\rm{b,max}}\le5\rm{ w}.$
  • ...and 2 more figures

Theorems & Definitions (3)

  • Lemma 1
  • Lemma 2
  • proof