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Beamforming in Secure Integrated Sensing and Communication Systems with Antenna Allocation

Yunxiang Shi, Lixin Li, Wensheng Lin, Wei Liang, Zhu Han

TL;DR

This design optimizes antenna allocation and beamforming at the DFBS, meeting minimum secrecy rate and power constraints, and proposes solvers based on alternating optimization for the non-convex design problem.

Abstract

In this paper, we consider joint antenna allocation and transmit beamforming design in secure integrated sensing and communication (ISAC) systems. A dual-function base station (DFBS) aims to securely deliver messages to a single-antenna receiver while detecting potential eavesdroppers. To prevent eavesdropping, we incorporate specialized sensing signals, intentionally reducing communication signal power toward suspicious targets to improve sensing. We prioritize minimizing the matching error between the transmitting and required beampatterns for sensing and communication. Our design optimizes antenna allocation and beamforming at the DFBS, meeting minimum secrecy rate and power constraints. We propose solvers based on alternating optimization for the non-convex design problem. Simulations show that the antenna allocation scheme significantly improves safety performance.

Beamforming in Secure Integrated Sensing and Communication Systems with Antenna Allocation

TL;DR

This design optimizes antenna allocation and beamforming at the DFBS, meeting minimum secrecy rate and power constraints, and proposes solvers based on alternating optimization for the non-convex design problem.

Abstract

In this paper, we consider joint antenna allocation and transmit beamforming design in secure integrated sensing and communication (ISAC) systems. A dual-function base station (DFBS) aims to securely deliver messages to a single-antenna receiver while detecting potential eavesdroppers. To prevent eavesdropping, we incorporate specialized sensing signals, intentionally reducing communication signal power toward suspicious targets to improve sensing. We prioritize minimizing the matching error between the transmitting and required beampatterns for sensing and communication. Our design optimizes antenna allocation and beamforming at the DFBS, meeting minimum secrecy rate and power constraints. We propose solvers based on alternating optimization for the non-convex design problem. Simulations show that the antenna allocation scheme significantly improves safety performance.
Paper Structure (12 sections, 1 theorem, 26 equations, 4 figures, 1 algorithm)

This paper contains 12 sections, 1 theorem, 26 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Signal Model
  4. Communication Model
  5. Sensing Model
  6. Problem Formulation
  7. Communication metrics
  8. Radar sensing metrics
  9. Design problems
  10. Proposed Method
  11. Simulation Results
  12. Conclusion

Key Result

Proposition 1

The optimal solution to problem (P5) is where $\hat{\bm{w}}_c=(\bm{h}^H_{bu} \bm{W}^{\ast}_c\bm{h}_{bu})^{-\frac{1}{2}} \bm{W}^{\ast}_c \bm{h}_{bu}$ denotes the corresponding transmit beamforming vector at the DFBS. Accordingly, $\hat{\bm{W}}_c$, $\hat{\bm{S}}$, $\hat{\mu}$ ,and $\hat{\bm{u}}$ are the optimal solution to problem (P5).

Figures (4)

  • Figure 1: A secure ISAC system with a ULA to perform communication and sensing functions.
  • Figure 2: Beampattern radiated power under different designs, where $R_0 = 5$bps/Hz, $P_{all} = 30$dBm.
  • Figure 3: Communication signals radiated power directed to untrusted targets versus the secrecy rate threshold $R_0$.
  • Figure 4: Target minimum radiated power and the communication signals radiated power with $R_0 = 5$bps/Hz.

Theorems & Definitions (2)

  • Proposition 1
  • proof