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Adaptive Sensing Performance Design for Enhancing Secure Communication in Networked ISAC Systems

Published: October 18, 2025 | arXiv ID: 2510.16397v1

By: Yiming Xu , Dongfang Xu , Shenghui Song and more

Potential Business Impact:

Keeps secret messages safe from spies.

Business Areas:
Application Specific Integrated Circuit (ASIC) Hardware

The channel state information (CSI) of an eavesdropper is crucial for physical layer security (PLS) design, but it is difficult to obtain due to the passive and non-cooperative nature of the eavesdropper. To this end, integrated sensing and communication (ISAC) offers a novel solution by estimating the CSI of the eavesdropper based on sensing information. However, existing studies normally impose explicit and fixed sensing performance requirement without considering the varying communication conditions, which hinders the system from fully exploiting the synergy between sensing and communication. To address this issue, this paper proposes sensing-enhanced secure communication with adaptive sensing performance. Specifically, we formulate the sensing performance implicitly in the information leakage rate and adaptively optimize it for the minimization of the power consumption, offering enhanced flexibility and adaptability in sensing performance. We consider both centralized and decentralized designs to thoroughly investigate the impact of network structure on system performance and complexity. Specifically, we devise a block coordinate descent (BCD)-based method for centralized design. For decentralized design, we develop an optimization framework based on consensus alternating direction method of multipliers (ADMM) to reduce complexity and information exchange overhead. Experimental results demonstrate the advantage of the proposed implicit sensing performance requirement design due to its capability to adaptively adjust the sensing performance to enhance the system performance for varying system configurations.

Country of Origin
πŸ‡ΈπŸ‡¬ πŸ‡­πŸ‡° Singapore, Hong Kong

Page Count
16 pages

Category
Electrical Engineering and Systems Science:
Signal Processing