Secure Spatial Signal Design for ISAC in a Cell-Free MIMO Network

TL;DR

This paper proposes a secure waveform design for cell-free MIMO networks with integrated sensing and communication, optimizing artificial noise to protect against eavesdroppers while maintaining system performance.

Contribution

It introduces a novel ISAC waveform model with artificial noise and an optimization framework for precoding and AN covariance matrices in a cell-free MIMO setting.

Findings

Optimal AN covariance is rank-1 with a peak towards the eavesdropper.

Trade-off exists between sensing accuracy and communication quality.

Inverse relationship between Eve's distance and CRB magnitude.

Abstract

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.