Multi-Vehicle Collaborative Sensing in RSMA-Assisted ISAC Systems

In this paper, we investigate a multi-vehicle collaborative sensing scheme in rate-splitting multiple access (RSMA) assisted integrated sensing and communication (ISAC) systems. To improve the sensing capability, sensing signals are transmitted to potential targets in the surrounding environment via the communicating vehicles. On this basis, the lower bound on the ergodic sum rate under imperfect channel state information for the communication system and the Cramér-Rao bound for the sensing system are derived. Furthermore, this paper aims to minimize the Cramér- Rao bound under the constraint of the sum rate by jointly optimizing the rate splitting ratio, the precoders, and the transmit power. Then, a semi-definite programming-based matrix-lifting algorithm is designed to solve the optimization problem. Numerical results illustrate the significant sensing performance boosted by multi-vehicle collaboration and demonstrate the superiority of our proposed scheme in trading off the communication and sensing performance.