面向多目标感知的RSMA辅助ISAC系统鲁棒波束成形设计OA

To address the degradation of beamforming performance caused by spectrum scarcity and imperfect channel state information in 6G systems,a robust beamforming design method was proposed for rate splitting multiple access(RSMA)-assisted integrated sensing and communication(ISAC)systems with multi-target sensing.Under the imperfect channel state information at the transmitter(CSIT)with a statistical error channel model,the radar sensing process was divided into target detection and target tracking stages.The Cramér-Rao bound(CRB)was adopted as the sensing metric,while the max-min average communication rate was employed as the fairness metric.Accordingly,a robust beamforming optimization problem for the RSMA-assisted ISAC system was formulated.To solve the uncertain non-convex optimiza-tion problem,a double-layer penalized iterative optimization algorithm based on sample average approximation(SAA)and successive convex approximation(SCA)was proposed.The original uncertain non-convex problem was transformed into a deterministic convex problem through SAA,semidefinite relaxation(SDR),and SCA methods.Simulation results demonstrate that,in the target tracking stage with M=2 and the signal-to-noise ratio(SNR)of 20 dB,the proposed scheme achieves approximately 14%improvement in user fair rate and 22%improvement in sensing accuracy compared with the space division multiple access(SDMA)-assisted ISAC scheme.