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UAV-Enabled Secure ISAC Against Dual Eavesdropping Threats: Joint Beamforming and Trajectory Design

Jianping Yao, Zeyu Yang, Zai Yang, Jie Xu, Tony Q. S. Quek

TL;DR

This work addresses secure ISAC from a UAV by jointly optimizing trajectory, communication beamforming, and sensing beamforming in the presence of a dual-function eavesdropper. It introduces an alternating-optimization framework that leverages SDR to relax rank constraints and SCA with trust-region techniques to convexify non-convex objectives and constraints, yielding tractable subproblems for both beamforming (3.1) and trajectory (3.2) updates. The main contributions are the development of a reliable reconstruction of rank-one beamformers from the relaxed solution and a convergent AO algorithm that achieves higher average secrecy rates while satisfying sensing performance and sensing-security constraints under UAV mobility and power limits. Numerical results show substantial secrecy-rate gains over baselines and illustrate the interplay between trajectory planning and beamforming in safeguarding both communication and sensing signals. ${R_s[n]}$ and related beampatterns are used to quantify performance, enabling practical assessment of security in UAV-enabled secure ISAC systems.}

Abstract

In this work, we study an unmanned aerial vehicle (UAV)-enabled secure integrated sensing and communication (ISAC) system, where a UAV serves as an aerial base station (BS) to simultaneously perform communication with a user and detect a target on the ground, while a dual-functional eavesdropper attempts to intercept the signals for both sensing and communication. Facing the dual eavesdropping threats, we aim to enhance the average achievable secrecy rate for the communication user by jointly designing the UAV trajectory together with the transmit information and sensing beamforming, while satisfying the requirements on sensing performance and sensing security, as well as the UAV power and flight constraints. To address the non-convex nature of the optimization problem, we employ the alternating optimization (AO) strategy, jointly with the successive convex approximation (SCA) and semidefinite relaxation (SDR) methods. Numerical results validate the proposed approach, demonstrating its ability to achieve a high secrecy rate while meeting the required sensing and security constraints.

UAV-Enabled Secure ISAC Against Dual Eavesdropping Threats: Joint Beamforming and Trajectory Design

TL;DR

This work addresses secure ISAC from a UAV by jointly optimizing trajectory, communication beamforming, and sensing beamforming in the presence of a dual-function eavesdropper. It introduces an alternating-optimization framework that leverages SDR to relax rank constraints and SCA with trust-region techniques to convexify non-convex objectives and constraints, yielding tractable subproblems for both beamforming (3.1) and trajectory (3.2) updates. The main contributions are the development of a reliable reconstruction of rank-one beamformers from the relaxed solution and a convergent AO algorithm that achieves higher average secrecy rates while satisfying sensing performance and sensing-security constraints under UAV mobility and power limits. Numerical results show substantial secrecy-rate gains over baselines and illustrate the interplay between trajectory planning and beamforming in safeguarding both communication and sensing signals. and related beampatterns are used to quantify performance, enabling practical assessment of security in UAV-enabled secure ISAC systems.}

Abstract

In this work, we study an unmanned aerial vehicle (UAV)-enabled secure integrated sensing and communication (ISAC) system, where a UAV serves as an aerial base station (BS) to simultaneously perform communication with a user and detect a target on the ground, while a dual-functional eavesdropper attempts to intercept the signals for both sensing and communication. Facing the dual eavesdropping threats, we aim to enhance the average achievable secrecy rate for the communication user by jointly designing the UAV trajectory together with the transmit information and sensing beamforming, while satisfying the requirements on sensing performance and sensing security, as well as the UAV power and flight constraints. To address the non-convex nature of the optimization problem, we employ the alternating optimization (AO) strategy, jointly with the successive convex approximation (SCA) and semidefinite relaxation (SDR) methods. Numerical results validate the proposed approach, demonstrating its ability to achieve a high secrecy rate while meeting the required sensing and security constraints.
Paper Structure (7 sections, 1 theorem, 51 equations, 5 figures)

This paper contains 7 sections, 1 theorem, 51 equations, 5 figures.

Table of Contents

  1. Introduction
  2. System Model
  3. Proposed Solution
  4. Optimization of Information and Sensing Beamforming
  5. UAV Trajectory Optimization
  6. Numerical Results
  7. Proof of Lemma \ref{['lemma1']}

Key Result

Lemma 1

With the converged solution ${\boldsymbol B}^*[n]$ and ${\boldsymbol A}^*_s[n]$ obtained by the SCA technique, we can always construct an alternative rank-one solution achieving the same optimal objective, given by where $\text{rank}({\bar{\boldsymbol{B}}}[n])=1$.

Figures (5)

  • Figure 1: Illustration of the UAV-enabled secure ISAC system.
  • Figure 2: Trajectories obtained by our proposed design and the benchmark without sensing security.
  • Figure 3: Power allocation between sensing and communication signals over time by our proposed design and the benchmark without sensing security.
  • Figure 4: Achieved beampattern gain at time slot $10$.
  • Figure 5: Average secrecy rate versus the antenna number $M$ over 100 Monte Carlo runs, where the locations of the eavesdropper and ground nodes are randomly generated within the desirable region $[200,400]\times[400,600]$.

Theorems & Definitions (2)

  • Lemma 1
  • Proof 1