Performance Analysis of Multi-Target ISAC System Based on Kullback–Leibler Divergence

This paper proposes a novel framework based on the Kullback-Leibler divergence (KLD) to quantify and analyse the performance trade-off between sensing and communication subsystems in an integrated sensing and communication (ISAC) system. We consider a multiple-input multiple-output (MIMO) base station (BS) that simultaneously serves communication user equipments (UEs) and detects multiple targets using shared antenna deployment. The zero-forcing (ZF) and the conventional identity covariance based beamforming are employed for the communication and the radar subsystems, respectively. Our framework exploits the inherent communication signals alongside dedicated radar signals for target detection, enhancing radar performance through this dual-use approach. The proposed KLDbased approach provides a unified performance measure that encompasses both the UE error rate and the target detection capability. Through theoretical derivations and simulations for both subsystems and beamforming techniques, we demonstrate the accuracy of the derived KLD in characterizing the performance trade-off under various system configurations. The findings of this study facilitate the holistic design of ISAC systems for nextgeneration wireless networks, offering insights into optimizing the balance between sensing and communication capabilities.