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Sensing-aided Near-Field Secure Communications with Mobile Eavesdroppers

Yiming Xu, Mingxuan Zheng, Dongfang Xu, Shenghui Song, Daniel Benevides da Costa

TL;DR

This paper tackles secure communication in near-field regimes with moving eavesdroppers by leveraging integrated sensing and communication (ISAC) to track the adversary via an extended Kalman filter. It formulates a multi-objective optimization problem that jointly optimizes transmit power and sensing energy, the number of securely served users, and the accuracy of tracking under rate and leakage constraints, and provides both a globally optimal solution using generalized Benders decomposition and a low-complexity ZF-SCA design. The proposed framework reveals that near-field beam diffraction and distance DoF can be exploited to focus information energy toward legitimate users while nulling energy around the eavesdropper, even under mobility. Numerical results validate convergence, Pareto optimality, and the practical efficacy of sensing-aided PLS, demonstrating significant performance gains and robust tracking under realistic mobility and uncertainty models.

Abstract

The additional degree of freedom (DoF) in the distance domain of near-field communication offers new opportunities for physical layer security (PLS) design. However, existing works mainly consider static eavesdroppers, and the related study with mobile eavesdroppers is still in its infancy due to the difficulty in obtaining the channel state information (CSI) of the eavesdropper. To this end, we propose to leverage the sensing capability of integrated sensing and communication (ISAC) systems to assist PLS design. To comprehensively study the dynamic behaviors of the system, we propose a Pareto optimization framework, where a multi-objective optimization problem (MOOP) is formulated to simultaneously optimize three key performance metrics: power consumption, number of securely served users, and tracking performance, while guaranteeing the achievable rate of the users with a given leakage rate constraint. A globally optimal design based on the generalized Benders decomposition (GBD) method is proposed to achieve the Pareto optimal solutions. To reduce the computational complexity, we further design a low-complexity algorithm based on zero-forcing (ZF) beamforming and successive convex approximation (SCA). Simulation results validate the effectiveness of the proposed algorithms and reveal the intrinsic trade-offs between the three performance metrics. It is observed that near-field communication offers a favorable beam diffraction effect for PLS, where the energy of the information signal is nulled around the eavesdropper and focused on the users.

Sensing-aided Near-Field Secure Communications with Mobile Eavesdroppers

TL;DR

This paper tackles secure communication in near-field regimes with moving eavesdroppers by leveraging integrated sensing and communication (ISAC) to track the adversary via an extended Kalman filter. It formulates a multi-objective optimization problem that jointly optimizes transmit power and sensing energy, the number of securely served users, and the accuracy of tracking under rate and leakage constraints, and provides both a globally optimal solution using generalized Benders decomposition and a low-complexity ZF-SCA design. The proposed framework reveals that near-field beam diffraction and distance DoF can be exploited to focus information energy toward legitimate users while nulling energy around the eavesdropper, even under mobility. Numerical results validate convergence, Pareto optimality, and the practical efficacy of sensing-aided PLS, demonstrating significant performance gains and robust tracking under realistic mobility and uncertainty models.

Abstract

The additional degree of freedom (DoF) in the distance domain of near-field communication offers new opportunities for physical layer security (PLS) design. However, existing works mainly consider static eavesdroppers, and the related study with mobile eavesdroppers is still in its infancy due to the difficulty in obtaining the channel state information (CSI) of the eavesdropper. To this end, we propose to leverage the sensing capability of integrated sensing and communication (ISAC) systems to assist PLS design. To comprehensively study the dynamic behaviors of the system, we propose a Pareto optimization framework, where a multi-objective optimization problem (MOOP) is formulated to simultaneously optimize three key performance metrics: power consumption, number of securely served users, and tracking performance, while guaranteeing the achievable rate of the users with a given leakage rate constraint. A globally optimal design based on the generalized Benders decomposition (GBD) method is proposed to achieve the Pareto optimal solutions. To reduce the computational complexity, we further design a low-complexity algorithm based on zero-forcing (ZF) beamforming and successive convex approximation (SCA). Simulation results validate the effectiveness of the proposed algorithms and reveal the intrinsic trade-offs between the three performance metrics. It is observed that near-field communication offers a favorable beam diffraction effect for PLS, where the energy of the information signal is nulled around the eavesdropper and focused on the users.
Paper Structure (20 sections, 5 theorems, 84 equations, 12 figures, 2 algorithms)

This paper contains 20 sections, 5 theorems, 84 equations, 12 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Signal Model
  4. Radar Measurement Model
  5. Tracking Scheme for Eavesdropper
  6. Channel Error Model
  7. Problem Formulation
  8. Pareto Optimal Solution of the MOOP
  9. Problem Transformation
  10. GBD-based Optimal Design
  11. Low-complexity Design
  12. Numerical Results
  13. Algorithm Convergence
  14. Optimal Pareto Boundary
  15. Impact of Beam Focusing and Beam Diffraction in Near-field Secure Communication
  16. ...and 5 more sections

Key Result

Lemma 1

(S-Procedure Lemma boyd2004convex) Define two functions $f_i(\mathbf{t}): \mathbb{C}^{N\times 1}\to \mathbb{R}$, $i\in \left \{ 1,2 \right \}$ as where $\mathbf{A}_i\in \mathbb{H}^N$, $\mathbf{b}_i\in \mathbb{C}^{N\times 1}$, and $\mathrm{c}_i\in \mathbb{R}$. Then, the implication $f_1(\mathbf{t})\leq0 \Rightarrow f_2(\mathbf{t})\leq0$ holds if and only if there exists a variable $\kappa \geq 0$

Figures (12)

  • Figure 1: Illustration of the considered secure near-field communication system.
  • Figure 2: The framework of the sensing-aided PLS design.
  • Figure 3: Simulation setup of a sensing-assisted near-field secure communication system with $K=7$ users, one eavesdropper and one BS.
  • Figure 4: Convergence of Algorithm 1 (Top) and Algorithm 2 (Bottom).
  • Figure 5: Optimal Pareto boundary.
  • ...and 7 more figures

Theorems & Definitions (7)

  • Definition 1
  • Definition 2
  • Lemma 1
  • Proposition 1
  • Lemma 2
  • Proposition 2
  • Lemma 3