In this paper, we study a cell-free multiple-input multiple-output network equipped with integrated sensing and communication (ISAC) access points (APs). The distributed APs are used to jointly serve the communication needs of user equipments (UEs) while sensing a target, assumed to be an eavesdropper (Eve). To increase the system's robustness towards said Eve, we develop an ISAC waveform model that includes artificial noise (AN) aimed at degrading the Eve channel quality. The central processing unit receives the observations from each AP and calculates the optimal precoding and AN covariance matrices by solving a semi-definite relaxation of a constrained Cramer-Rao bound (CRB) minimization problem. Simulation results highlight an underlying trade-off between sensing and communication performances: in particular, the UEs signal-to-noise and interference ratio and the maximum Eve's signal to noise ratio are directly proportional to the CRB. Furthermore, the optimal AN covariance matrix is rank-1 and has a peak in the eve's direction, leading to a surprising inverse-proportionality between the UEs-Eve distance and optimal-CRB magnitude.

翻译：本文研究了一种配备集成感知与通信（ISAC）接入点（APs）的细胞自由多输入多输出网络。分布式APs用于联合服务于用户设备（UEs）的通信需求，同时感知一个假设为窃听者（Eve）的目标。为增强系统对该窃听者的鲁棒性，我们开发了一种包含人工噪声（AN）的ISAC波形模型，旨在降低Eve信道质量。中央处理单元接收来自各AP的观测数据，并通过求解约束克拉美-罗界（CRB）最小化问题的半定松弛，计算出最优预编码和AN协方差矩阵。仿真结果揭示了感知与通信性能之间的内在权衡：具体而言，UEs的信噪干扰比及Eve最大信噪比与CRB直接成正比。此外，最优AN协方差矩阵为秩1矩阵，并在Eve方向上形成峰值，导致UEs与Eve间距与最优CRB幅度之间呈现反比关系。