This paper considers an active reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system. We aim to maximize radar signal-to-interference-plus-noise-ratio (SINR) by jointly optimizing the beamforming matrix at the dual-function radar-communication (DFRC) base station (BS) and the reflecting coefficients at the active RIS subject to the quality of service (QoS) constraints of communication users (UE) and the transmit power constraints of active RIS and DFRC BS. To tackle the optimization problem, the majorization-minimization (MM) algorithm is applied to address the nonconvex radar SINR objective function, and the resulting quartic problem is solved by developing an semidefinite relaxation (SDR)-based approach. Moreover, we derive the scaling order of the radar SINR with a large number of reflecting elements. Next, the transmit power allocation problem and the deployment strategy of the active RIS are studied with a moderate number of reflecting elements. Finally, we validate the potential of the active RIS in ISAC systems compared to passive RIS. Additionally, we deliberate on several open problems that remain for future research.

翻译：本文研究了一种有源可重构智能表面（RIS）辅助的集成感知与通信（ISAC）系统。我们旨在通过联合优化双功能雷达通信（DFRC）基站（BS）处的波束赋形矩阵和有源RIS处的反射系数，在满足通信用户（UE）的服务质量（QoS）约束以及有源RIS和DFRC BS的发射功率约束的条件下，最大化雷达信号与干扰加噪声比（SINR）。为处理该优化问题，我们采用多数化-最小化（MM）算法来求解非凸的雷达SINR目标函数，并通过开发一种基于半定松弛（SDR）的方法来求解由此产生的四次问题。此外，我们推导了在大规模反射单元下雷达SINR的缩放规律。接着，针对中等数量反射单元的场景，研究了发射功率分配问题及有源RIS的部署策略。最后，我们验证了与无源RIS相比，有源RIS在ISAC系统中的潜力。同时，本文还探讨了若干有待未来研究的开放性问题。