I-RIS辅助RSMA-ISAC系统能效优化研究OA

To address the challenges of limited coverage,complex multi-user interference,and low energy efficiency in millimeter-wave integrated sensing and communication systems,a rate-splitting multiple access energy efficiency optimization scheme based on irregular intelligent reflecting surfaces was proposed.Unlike traditional full-array activation modes,the irregular intelligent reflecting surfaces significantly reduce hardware power consumption while ensuring virtual link quality through sparse topology optimization.Meanwhile,rate-splitting multiple access achieves flexible interference management by dividing messages into common and private streams.Under the constraints of sensing signal-to-noise ratio and communication quality of service,the intelligent reflecting surfaces'sparse topology,rate-splitting precoding matrix and phase shift matrix were jointly optimized to maximize system energy efficiency.For this hybrid nonlinear programming problem,a two-layer optimization framework was proposed.The outer layer employed an improved genetic-tabu search algorithm to efficiently explore the optimal topology structure,while the inner layer alternately solved the precoding and phase shift design by combining fractional programming,weighted minimum mean square error and Riemann manifold optimization algorithms.Simulation results demonstrate that the proposed scheme achieves an 18%energy efficiency gain over traditional intelligent reflecting surface schemes at typical operating points,with particularly notable advantages in high-load scenarios due to the rate-splitting access technology used in this study.Perceptual beam analysis further validates the unique benefits of the rate-splitting scheme in enhancing sensing performance,achieving a 6.9 dB sensing gain improvement compared to traditional schemes.