Localization plays an increasingly pivotal role in 5G/6G systems, enabling various applications. This paper focuses on the privacy concerns associated with delay-based localization, where unauthorized base stations attempt to infer the location of the end user. We propose a method to disrupt localization at unauthorized nodes by injecting artificial components into the pilot signal, exploiting model mismatches inherent in these nodes. Specifically, we investigate the effectiveness of two techniques, namely artificial multipath (AM) and artificial noise (AN), in mitigating location leakage. By leveraging the misspecified Cram\'er-Rao bound framework, we evaluate the impact of these techniques on unauthorized localization performance. Our results demonstrate that pilot manipulation significantly degrades the accuracy of unauthorized localization while minimally affecting legitimate localization. Moreover, we find that the superiority of AM over AN varies depending on the specific scenario.

翻译：定位技术在5G/6G系统中扮演着日益关键的角色，支撑着多种应用场景。本文聚焦于基于时延的定位技术所引发的隐私问题，即未经授权的基站试图推断终端用户的位置。我们提出一种通过在导频信号中注入人工分量以破坏未授权节点定位能力的方法，该方法利用了这些节点固有的模型失配特性。具体而言，我们研究了人工多径（AM）与人工噪声（AN）两种技术在抑制位置信息泄露方面的有效性。通过利用误设定克拉美-罗界分析框架，我们评估了这些技术对未授权定位性能的影响。实验结果表明，导频操控能显著降低未授权定位的精度，同时对合法定位的影响极小。此外，我们发现AM相对于AN的优越性会因具体场景而异。