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Secure ISAC MIMO Systems: Exploiting Interference With Bayesian Cramér-Rao Bound Optimization

Nanchi Su, Fan Liu, Christos Masouros, George C. Alexandropoulos, Yifeng Xiong, Qinyu Zhang

TL;DR

This work tackles secure ISAC by formulating a BCRB-minimization problem for target sensing under a QoS constraint for multiple users, while enforcing destructive interference at potential eavesdroppers through a CI-DI signaling strategy. A tailored SCA-based algorithm solves the nonconvex optimization, decomposing the destructive interference region into linear subproblems and iteratively updating the transmit signal matrix $\mathbf{X}$. The proposed CI-DI design outperforms traditional block-level precoding, achieving tighter sensing beampatterns and higher secrecy, as evidenced by SER behavior at eavesdroppers and the CU performance–sensing tradeoff. Overall, the approach provides a practical framework for secure, high-performance ISAC using symbol-level optimization and prior-knowledge-driven sensing.

Abstract

In this paper, we present a signaling design for secure integrated sensing and communication (ISAC) systems comprising a dual-functional multi-input multi-output (MIMO) base station (BS) that simultaneously communicates with multiple users while detecting targets present in their vicinity, which are regarded as potential eavesdroppers. In particular, assuming that the distribution of each parameter to be estimated is known \textit{a priori}, we focus on optimizing the targets' sensing performance. To this end, we derive and minimize the Bayesian Cramér-Rao bound (BCRB), while ensuring certain communication quality of service (QoS) by exploiting constructive interference (CI). The latter scheme enforces that the received signals at the eavesdropping targets fall into the destructive region of the signal constellation, to deteriorate their decoding probability, thus enhancing the ISAC's system physical-layer security (PLS) capability. To tackle the nonconvexity of the formulated problem, a tailored successive convex approximation method is proposed for its efficient solution. Our extensive numerical results verify the effectiveness of the proposed secure ISAC design showing that the proposed algorithm outperforms block-level precoding techniques.

Secure ISAC MIMO Systems: Exploiting Interference With Bayesian Cramér-Rao Bound Optimization

TL;DR

This work tackles secure ISAC by formulating a BCRB-minimization problem for target sensing under a QoS constraint for multiple users, while enforcing destructive interference at potential eavesdroppers through a CI-DI signaling strategy. A tailored SCA-based algorithm solves the nonconvex optimization, decomposing the destructive interference region into linear subproblems and iteratively updating the transmit signal matrix . The proposed CI-DI design outperforms traditional block-level precoding, achieving tighter sensing beampatterns and higher secrecy, as evidenced by SER behavior at eavesdroppers and the CU performance–sensing tradeoff. Overall, the approach provides a practical framework for secure, high-performance ISAC using symbol-level optimization and prior-knowledge-driven sensing.

Abstract

In this paper, we present a signaling design for secure integrated sensing and communication (ISAC) systems comprising a dual-functional multi-input multi-output (MIMO) base station (BS) that simultaneously communicates with multiple users while detecting targets present in their vicinity, which are regarded as potential eavesdroppers. In particular, assuming that the distribution of each parameter to be estimated is known \textit{a priori}, we focus on optimizing the targets' sensing performance. To this end, we derive and minimize the Bayesian Cramér-Rao bound (BCRB), while ensuring certain communication quality of service (QoS) by exploiting constructive interference (CI). The latter scheme enforces that the received signals at the eavesdropping targets fall into the destructive region of the signal constellation, to deteriorate their decoding probability, thus enhancing the ISAC's system physical-layer security (PLS) capability. To tackle the nonconvexity of the formulated problem, a tailored successive convex approximation method is proposed for its efficient solution. Our extensive numerical results verify the effectiveness of the proposed secure ISAC design showing that the proposed algorithm outperforms block-level precoding techniques.
Paper Structure (6 sections, 29 equations, 4 figures, 1 algorithm)

This paper contains 6 sections, 29 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. Signal Model
  3. Problem Formulation
  4. Proposed Secure ISAC Signaling Design
  5. Numerical Results and Discussion
  6. Conclusion

Figures (4)

  • Figure 1: The constellation of received signals at CUs, a) QPSK, b) 8PSK, $K_{cu}=3, K_{tar}=2, P_0=30\;\text{dBm}, \Gamma_{\rm{CU}, k} = 15\;\text{dB}, \forall\;k, \tau_{\rm{E},n} = -5\;\text{dB}$, and $\sigma_{\theta_n} = 5^\circ, \forall\;n$.
  • Figure 2: The resultant beampatterns via the proposed secure ISAC signaling design with different a priori information of the angle, a) standard deviation is $1^\circ$, b) standard deviation is $5^\circ$, $K_{cu}=3, K_{tar}=2, P_0=30\;\text{dBm}$, $\Gamma_{\rm{CU},k} = 20\;\text{dB} \forall\;k$.
  • Figure 3: Performance tradeoff between the communication and sensing systems with different power budgets, for $K_{cu}=3$ and $K_{tar}=2$.
  • Figure 4: SER of CUs and average SER of targets/Eves versus the SNR threshold $\Gamma_{\rm{CU},k}$ with different power budgets for $K_{cu}=3$ and $K_{tar}=2$.