STARS Enabled Integrated Sensing and Communications: A CRB optimization Perspective

Abstract

A simultaneously transmitting and reflecting intelligent surface (STARS) enabled integrated sensing and communications (ISAC) framework is proposed, where the whole space is divided by STARS into a sensing space and a communication space. A novel sensing-at-STARS structure, where dedicated sensors are installed at the STARS, is proposed to address the significant path loss and clutter interference for sensing. The Cramér-Rao bound (CRB) of the 2-dimension (2D) direction-of-arrivals (DOAs) estimation of the sensing target is derived, which is then minimized subject to the minimum communication requirement. A novel approach is proposed to transform the complicated CRB minimization problem into a trackable modified Fisher information matrix (FIM) optimization problem. Moreover, to address the coupled issue in the modified FIM, an efficient double-loop iterative algorithm based on the penalty dual decomposition method is conceived. The numerical results demonstrate that: 1) STARS significantly outperforms the conventional transmitting/reflecting-only intelligent surface; 2) High sensing accuracy can be achieved by STARS using the practical 2D maximum likelihood estimator.