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Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

Yuchen Zhang, Wanli Ni, Jianquan Wang, Wanbin Tang, Min Jia, Yonina C. Eldar, Dusit Niyato

TL;DR

This work addresses robust covert ISAC transceiver design under imperfect CSI by formulating worst-case (bounded) and outage-constrained (probabilistic) problems that jointly optimize transmit beamforming and radar waveform with a covert-communication constraint. It employs S-procedure and Bernstein-type inequalities to convert semi-infinite constraints into finite LMIs and SOCs, and introduces an alternating double-checking (ADC) framework that decouples transmitter and receiver designs while enforcing rank-one solutions via matrix lifting. The approach reveals a tripartite trade-off among radar performance, overt communications, and covert communications, and shows that receiver-side beamforming significantly enhances radar SINR beyond transmitter-centric designs. Numerical results demonstrate fast convergence, robust performance gains, and the crucial role of receiver processing in covert ISAC systems. The proposed framework offers a practical pathway for designing secure, efficient, and robust ISAC systems in the presence of realistic CSI uncertainties.

Abstract

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint trasceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems.

Robust Transceiver Design for Covert Integrated Sensing and Communications With Imperfect CSI

TL;DR

This work addresses robust covert ISAC transceiver design under imperfect CSI by formulating worst-case (bounded) and outage-constrained (probabilistic) problems that jointly optimize transmit beamforming and radar waveform with a covert-communication constraint. It employs S-procedure and Bernstein-type inequalities to convert semi-infinite constraints into finite LMIs and SOCs, and introduces an alternating double-checking (ADC) framework that decouples transmitter and receiver designs while enforcing rank-one solutions via matrix lifting. The approach reveals a tripartite trade-off among radar performance, overt communications, and covert communications, and shows that receiver-side beamforming significantly enhances radar SINR beyond transmitter-centric designs. Numerical results demonstrate fast convergence, robust performance gains, and the crucial role of receiver processing in covert ISAC systems. The proposed framework offers a practical pathway for designing secure, efficient, and robust ISAC systems in the presence of realistic CSI uncertainties.

Abstract

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint trasceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems.
Paper Structure (16 sections, 3 theorems, 39 equations, 4 figures, 2 tables, 2 algorithms)

This paper contains 16 sections, 3 theorems, 39 equations, 4 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Related Works
  3. Motivations and Contributions
  4. System Model
  5. Communications and Radar Performances
  6. Detection Performance and Covertness Constraint
  7. Channel Error Model
  8. Worst-Case Robust Design Under Bounded Error Model
  9. Problem Formulation
  10. Problem Reformulation
  11. Proposed Transceiver Design Framework
  12. Outage-Constrained Robust Design Under Probabilistic Error Model
  13. Problem Formulation
  14. Problem Reformulation and Solving
  15. Numerical Results
  16. ...and 1 more sections

Key Result

Lemma 1

(S-Proceduregui2020tsp): Define the quadratic functions w.r.t. $\mathbf{x} \in \mathbb{C}^{M \times 1}$ as where $\mathbf{A}_{m} \in \mathbb{C}^{M \times M}$, $\mathbf{b}_{m} \in \mathbb{C}^{M \times 1}$, and $c_{m} \in \mathbb{R}$. The condition $f_{1} \le 0 \Rightarrow f_{2} \le 0$ holds if and only if there exists a variable $\omega \ge 0$ such that

Figures (4)

  • Figure 1: Illustration of the covert ISAC system with $T$ radar targets, $K_{o}$ overt communications users, $K_{c}$ covert communications users, and $C$ signal-dependent clutters.
  • Figure 2: Illustration of algorithmic convergence. (a) Comparison between the considered covert ISAC system and the radar-only upper bound. (b) Different uncertainty coefficients. (c) Different transmit antenna numbers. (d) Different receive antenna numbers.
  • Figure 3: Beampatterns. (a) Transmit beampattern under BE. (a) Receive beampattern under BE. (c) Transmit beampattern under PE. (d) Receive beampattern under PE.
  • Figure 4: (a) and (b) are the minimum radar SINR versus communications SINR requirement with perfect CSI for different overt user numbers and receive antenna numbers, respectively. (c) and (d) are the minimum radar SINR versus covert communications SINR for different uncertainty coefficients and overt communications SINRs, respectively. (e) and (f) are the minimum radar SINR versus receive antenna numbers for different uncertainty coefficients and transmit antenna numbers, respectively.

Theorems & Definitions (3)

  • Lemma 1
  • Lemma 2
  • Lemma 3