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）接入点的无蜂窝多输入多输出网络。分布式接入点被用于协同服务用户设备的通信需求，同时感知一个被假定为窃听者的目标。为增强系统对该窃听者的鲁棒性，我们提出了一种包含人工噪声的ISAC波形模型，旨在降低窃听信道的质量。中央处理单元接收来自各接入点的观测数据，并通过求解约束克拉美-罗界最小化问题的半定松弛形式，计算最优预编码矩阵与人工噪声协方差矩阵。仿真结果揭示了感知与通信性能间的内在权衡：具体而言，用户设备的信干噪比与窃听者最大信噪比均与克拉美-罗界值成正比。此外，最优人工噪声协方差矩阵具有秩1特性，并在窃听方向形成峰值，这导致用户设备与窃听者距离同最优克拉美-罗界值之间呈现令人意外的反比关系。