This paper delves into an integrated sensing and communication (ISAC) system bolstered by a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS). Within this system, a base station (BS) is equipped with communication and radar capabilities, enabling it to communicate with ground terminals (GTs) and concurrently probe for echo signals from a target of interest. Moreover, to manage interference and improve communication quality, the rate splitting multiple access (RSMA) scheme is incorporated into the system. The signal-to-interference-plus-noise ratio (SINR) of the received sensing echo signals is a measure of sensing performance. We formulate a joint optimization problem of common rates, transmit beamforming at the BS, and passive beamforming vectors of the STAR-RIS. The objective is to maximize sensing SINR while guaranteeing the communication rate requirements for each GT. We present an iterative algorithm to address the non-convex problem by invoking Dinkelbach's transform, semidefinite relaxation (SDR), majorization-minimization, and sequential rank-one constraint relaxation (SROCR) theories. Simulation results manifest that the performance of the studied ISAC network enhanced by the STAR-RIS and RSMA surpasses other benchmarks considerably. The results evidently indicate the superior performance improvement of the ISAC system with the proposed RSMA-based transmission strategy design and the dynamic optimization of both transmission and reflection beamforming at STAR-RIS.

翻译：本文深入研究了由同时透射与反射可重构智能表面（STAR-RIS）增强的集成感知与通信（ISAC）系统。在该系统中，基站（BS）兼具通信与雷达功能，使其能够与地面终端（GTs）进行通信，并同时探测来自感兴趣目标的回波信号。此外，为管理干扰并提升通信质量，系统引入了速率分割多址接入（RSMA）方案。接收到的感知回波信号的信干噪比（SINR）是衡量感知性能的指标。我们构建了一个关于公共速率、基站发射波束赋形以及STAR-RIS无源波束赋形矢量的联合优化问题。其目标是在保证每个地面终端通信速率需求的前提下，最大化感知信干噪比。我们提出了一种迭代算法，通过引入丁克尔巴赫变换、半定松弛（SDR）、最大化-最小化以及序列秩一约束松弛（SROCR）理论来解决这一非凸问题。仿真结果表明，由STAR-RIS和RSMA增强的所研究ISAC网络的性能显著超越了其他基准方案。结果明确表明，采用所提出的基于RSMA的传输策略设计以及STAR-RIS透射与反射波束赋形的动态优化，能够为ISAC系统带来显著的性能提升。