This paper investigates an intelligent reflecting surface (IRS) aided millimeter-wave integrated sensing and communication (ISAC) system. Specifically, based on the passive beam scanning in the downlink, the IRS finds the optimal beam for reflecting the signals from the base station to a communication user. Meanwhile, the IRS estimates the angle of a nearby target based on its echo signal received by the sensing elements mounted on the IRS (i.e., semi-passive IRS). We propose an ISAC protocol for achieving the above objective via simultaneous (beam) training and sensing (STAS). Then, we derive the achievable rate of the communication user and the Cramer-Rao bound (CRB) of the angle estimation for the sensing target in closed-form. The achievable rate and CRB exhibit different performance against the duration of beam scanning. Specifically, the average achievable rate initially rises and subsequently declines, while the CRB monotonically decreases. Consequently, the duration of beam scanning should be carefully selected to balance communication and sensing performance. Simulation results have verified our analytical findings and shown that, thanks to the efficient use of downlink beam scanning signal for simultaneous communication and target sensing, the STAS protocol outperforms the benchmark protocol with orthogonal beam training and sensing.

翻译：本文研究了智能反射面（IRS）辅助的毫米波一体化感知与通信（ISAC）系统。具体而言，基于下行链路中的被动波束扫描，IRS为将基站信号反射至通信用户而确定最优波束。与此同时，IRS根据其搭载的感知元件（即半被动IRS）接收到的目标回波信号，估计附近目标的角度。我们提出了一种通过同步（波束）训练与感知（STAS）实现上述目标的ISAC协议。随后，我们以闭式推导了通信用户的可达速率以及感知目标角度估计的克拉美-罗界（CRB）。可达速率与CRB随波束扫描时长的变化呈现不同性能特征：平均可达速率先升后降，而CRB单调递减。因此，需谨慎选择波束扫描时长以平衡通信与感知性能。仿真结果验证了我们的理论分析，并表明得益于下行链路波束扫描信号在通信与感知中的高效协同利用，STAS协议优于采用正交波束训练与感知的基准协议。