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arXiv 2210.08286eess.SP
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传感辅助的EARDROPPER估算:物理层安全性的ISAC突破

Sensing-Assisted Eavesdropper Estimation: An ISAC Breakthrough in Physical Layer Security

Nanchi Su, Fan Liu, Christos Masouros

摘要:

本文研究了面向通感一体化(ISAC)系统的传感辅助物理层安全(PLS)。PLS的一个众所周知的限制是需要有关于潜在窃听者(Eves)的信息。ISAC的感测功能在这里提供了一个使能作用,通过估计潜在的Eves的方向来通知PLS。在我们的方法中,ISAC基站(BS)首先发射一个全向波形,通过采用Capon和近似最大似然(CAML)技术相结合的搜索潜在的Eves的方向。使用由此产生的信息,潜在的夏娃,我们制定保密率的表达式,这是一个功能的夏娃的估计精度。然后,我们制定了一个加权优化问题,同时最大化的保密率和最小化的CRB的人工噪声(AN)的帮助下,和最小化的CRB的目标/Eves的估计。通过考虑可能的估计误差,我们实施了一个波束方向图约束,覆盖所有可能的方向的Eves宽的主波束。这意味着需要在所有这些方向上加强安全。通过提高估计准确度,感测和安全功能提供了相互的益处,导致随着优化的每次迭代的相互性能的提高,直到收敛。我们的研究结果利用这些互利,并揭示了实用的PLS传感作为一个使能器的有用性。

英文摘要:

In this paper, we investigate the sensing-aided physical layer security (PLS) towards Integrated Sensing and Communication (ISAC) systems. A well-known limitation of PLS is the need to have information about potential eavesdroppers (Eves). The sensing functionality of ISAC offers an enabling role here, by estimating the directions of potential Eves to inform PLS. In our approach, the ISAC base station (BS) firstly emits an omni-directional waveform to search for potential Eves' directions by employing the combined Capon and approximate maximum likelihood (CAML) technique. Using the resulting information about potential Eves, we formulate secrecy rate expressions, that are a function of the Eves' estimation accuracy. We then formulate a weighted optimization problem to simultaneously maximize the secrecy rate and minimize the CRB with the aid of the artificial noise (AN), and minimize the CRB of targets'/Eves' estimation. By taking the possible estimation errors into account, we enforce a beampattern constraint with a wide main beam covering all possible directions of Eves. This implicates that security needs to be enforced in all these directions. By improving estimation accuracy, the sensing and security functionalities provide mutual benefits, resulting in improvement of the mutual performances with every iteration of the optimization, until convergence. Our results avail of these mutual benefits and reveal the usefulness of sensing as an enabler for practical PLS.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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