论文标题
在混乱环境中针对IRS辅助的集成感应和通信系统的优化设计
Optimized Design for IRS-Assisted Integrated Sensing and Communication Systems in Clutter Environments
论文作者
论文摘要
在本文中，我们研究了在混乱环境中智能反射表面（IRS）辅助的集成感应和通信（ISAC）系统设计。在配备有统一线性阵列（ULA）的IRS的协助下，多个Antenna基站（BS）的目标是与多个通信用户（CUS）交流并同时感测多个目标。我们考虑使用IRS辅助的ISAC设计，在I型或II型CU中，每个类型I和类型II Cu可以分别从传感信号中取消干扰。 In particular, we aim to maximize the minimum sensing beampattern gain among multiple targets, by jointly optimizing the BS transmit beamforming vectors and the IRS phase shifting matrix, subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each Type-I/Type-II CU, the interference power constraint per clutter, the transmission power constraint at the BS, and the cross-correlation pattern constraint.由于BS的传输设计变量和IRS的相位变化矩阵的耦合，因此在类型I/类型II型的情况下，配制的MAX-MIN IRS辅助ISAC设计问题是高度非convex。因此，我们提出了一种有效的算法，基于交替优化和半定位弛豫（SDR）技术。在使用I型CU的情况下，我们表明BS处的专用传感信号总是有益于提高感应性能。相比之下，I型II CUS不需要BS处的专用传感信号。提供了数值结果，以表明拟议的IRS辅助ISAC设计方案比现有基准方案获得了显着增益。
In this paper, we investigate an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system design in a clutter environment. Assisted by an IRS equipped with a uniform linear array (ULA), a multi-antenna base station (BS) is targeted for communicating with multiple communication users (CUs) and sensing multiple targets simultaneously. We consider the IRS-assisted ISAC design in the case with Type-I or Type-II CUs, where each Type-I and Type-II CU can and cannot cancel the interference from sensing signals, respectively. In particular, we aim to maximize the minimum sensing beampattern gain among multiple targets, by jointly optimizing the BS transmit beamforming vectors and the IRS phase shifting matrix, subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each Type-I/Type-II CU, the interference power constraint per clutter, the transmission power constraint at the BS, and the cross-correlation pattern constraint. Due to the coupling of the BS's transmit design variables and the IRS's phase shifting matrix, the formulated max-min IRS-assisted ISAC design problem in the case with Type-I/Type-II CUs is highly non-convex. As such, we propose an efficient algorithm based on the alternating-optimization and semi-definite relaxation (SDR) techniques. In the case with Type-I CUs, we show that the dedicated sensing signal at the BS is always beneficial to improve the sensing performance. By contrast, the dedicated sensing signal at the BS is not required in the case with Type-II CUs. Numerical results are provided to show that the proposed IRS-assisted ISAC design schemes achieve a significant gain over the existing benchmark schemes.
