Resource Allocation for Intelligent Reflecting Surface Enabled Target Tracking in Integrated Sensing and Communication Systems

Abstract

Intelligent reflecting surface (IRS) is a promising enabler for achieving communication quality of service (QoS) and enhancing sensing QoS in Integrated Sensing and Communication (ISAC) systems. It has been regarded as one of the most attractive solutions for facilitating vehicle applications in internet of vehicles (IoV) by utilizing ISAC technologies. In this paper, the trajectory of target vehicle goes through no obstacle blocking stage and obstacle blocking stage successively in ISAC systems. And the performance trad-off is pursued in the sensing QoS and the communication QoS of the target vehicle. The achievable rate and posterior Cramer-Rao lower bounds (PCRLBs) are defined to reflect communication QoS and sensing QoS, respectively. In this process, the trade-off strategy on QoS for communication and IRS assisted sensing is explored in IoV. Hence, an optimization problem is designed to ensure communication capability of the target while ensuring its sensing ability. The joint semidefinite relaxation (SDR) and alternating optimization (AO) method is proposed to obtain the optimal solution on resource allocation (RA) and IRS phase shift. Simulation results verify the effectiveness of the proposed method in terms of performance trade-off between communication QoS and sensing QoS.

Keywords

• Intelligent reflecting surface
• integrated sensing and communication
• resource allocation
• posterior Cramer-Rao lower bounds
• quality of service