论文标题
与收发器硬件障碍的IRS辅助通信的优化优化
Beamforming Optimization for IRS-Aided Communications with Transceiver Hardware Impairments
论文作者
论文摘要
在本文中,我们专注于智能反射表面(IRS)辅助的多安丹娜通信,并在实践中遇到的收发器硬件障碍。特别是,我们旨在考虑硬件障碍的影响,以最大化接收到的信噪比(SNR),其中源传输光束成形和IRS反射光束成形是在建议的优化框架下共同设计的。为了避免公式设计问题的非跨性别性,我们首先是为源传输光束形成的封闭形式的最佳解决方案。然后,为了优化IRS,通过解决单个凸问题,我们获得了与最佳客观值的上限。开发了低复杂性次要最大化(MM)算法以接近上限。仿真结果表明,所提出的波束形成设计对硬件障碍比传统的SNR最大化方案更强大。此外,与不部署IRS的情况相比,通过纳入硬件障碍而带来的性能提高对于IRS辅助通信更为明显。
In this paper, we focus on intelligent reflecting surface (IRS) assisted multi-antenna communications with transceiver hardware impairments encountered in practice. In particular, we aim to maximize the received signal-to-noise ratio (SNR) taking into account the impact of hardware impairments, where the source transmit beamforming and the IRS reflect beamforming are jointly designed under the proposed optimization framework. To circumvent the non-convexity of the formulated design problem, we first derive a closed-form optimal solution to the source transmit beamforming. Then, for the optimization of IRS reflect beamforming, we obtain an upper bound to the optimal objective value via solving a single convex problem. A low-complexity minorization-maximization (MM) algorithm was developed to approach the upper bound. Simulation results demonstrate that the proposed beamforming design is more robust to the hardware impairments than that of the conventional SNR maximized scheme. Moreover, compared to the scenario without deploying an IRS, the performance gain brought by incorporating the hardware impairments is more evident for the IRS-aided communications.