通过联合信号与人工噪声波束成形增强ISAC中的感知隐私
Enhancing Sensing Privacy in ISAC Through Joint Signal and Artificial Noise Beamforming
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中文总结 AI 辅助
本研究针对6G中单基地ISAC系统的感知隐私问题，提出联合信号与人工噪声波束成形优化方法，通过迭代算法求解以降低未知位置感知窃听者的性能，保障用户位置隐私。
中文摘要 AI 辅助
集成感知与通信（ISAC）是6G网络中极具前景的特性，有望提升频谱效率并提供满足未来应用严苛要求的感知与通信服务。然而，这也带来了新的安全与隐私问题，使恶意攻击者可获取网络的新信息。本研究关注单基地ISAC系统的感知隐私，研究位置未知的感知窃听者（EVE）作为被动双基地雷达（PBR）获取用户位置信息的能力；随后提出联合发射与人工噪声（AN）波束成形优化问题以降低EVE的性能；最终提出迭代算法求解该优化问题并评估其性能。
英文摘要
Integrated sensing and communications (ISAC) is a promising feature in 6G networks. It is envisioned to enhance spectral efficiency and provide sensing and communication services that meet the stringent requirements of future applications. However, it also poses new security and privacy concerns by giving malicious attackers access to new information about the network. In this work, we focus on the sensing privacy of a monostatic ISAC system by investigating the capability of a sensing eavesdropper (EVE) with an unknown location, acting as a passive bistatic radar (PBR) to gain access to user location information. We then propose a joint transmit and artificial noise (AN) beamforming optimization problem to degrade EVE's performance. Finally, we propose an iterative algorithm to solve the proposed optimization problem and evaluate its performance.
