Cooperative ISAC With Direct Localization and Rate-Splitting Multiple Access Communication: A Pareto Optimization Framework

Integrated sensing and communication (ISAC) has been a promising technology in beyond 5G and 6G network to simultaneously support high-speed information transfer and high-quality environmental perception. Cloud radio access networks (C-RAN) enables the cooperation among multiple base stations (BSs) to provide additional cooperation gains for both communication and sensing functionalities. In this paper, we investigate the cooperative ISAC (CoISAC) system with rate-splitting multiple access (RSMA) transmission scheme for advanced interference management and direct localization sensing scheme to provide high-accuracy positioning services. Specifically, we adopt Pareto optimization framework to characterize the achievable performance region of the CoISAC system built on the sum rate of multiple communication users and the positioning error bound of radar target. Then, we formulate communication-centric and radar-centric optimization problems in the CoISAC system to systematically search for the optimal Pareto boundary of the achievable performance region. Two iterative algorithms based on successive convex approximation (SCA) are proposed to effectively solve these two optimization problems, respectively, therefore near-optimal Pareto boundary can be found. Numerical results show that the RSMA-assisted CoISAC system achieves the best trade-off performance among various baselines. The cooperative scheme can fully unveil the potential of RSMA in the ISAC system by providing more freedom for rate-splitting policy design under limited resources. Therefore, incorporating RSMA in the CoISAC system can significantly boost the overall performance.