[论文解读] Beamforming Designs and Performance Evaluations for Intelligent Reflecting Surface Enhanced Wireless Communication System with Hardware Impairments.

Yiming Liu, Erwu Liu+2 more|arXiv (Cornell University)|Jun 1, 2020

Advanced Wireless Communication Technologies参考文献 1被引用 15

一句话总结

本文提出了一种在硬件受限条件下，针对智能反射面（IRS）辅助无线系统的一种低复杂度波束成形设计，采用线性最小均方误差（LMMSE）信道估计和基于梯度下降的反射波束成形算法。结果表明，即使存在实际的硬件非理想性，也能在不使用昂贵高精度硬件的情况下实现高 spectral 效率和能量效率。

ABSTRACT

Intelligent reflecting surface (IRS) can effectively control the wavefront of the impinging signals, and has emerged as a promising way to improve the energy and spectrum efficiency of wireless communication systems. Most existing studies were conducted with an assumption that the hardware operations are perfect without any impairment. However, both physical transceiver and IRS suffer from non-negligible hardware impairments in practice, which will bring some major challenges, e.g., increasing the difficulty and complexity of the beamforming designs, and degrading the system performance. In this paper, by taking hardware impairments into consideration, we make the transmit and reflect beamforming designs and evaluate the system performance. First, we utilize the linear minimum mean square error estimator to make the channel estimations, and analyze the factors that affect estimation accuracy. Then, we derive the optimal transmit beamforming vector, and propose a gradient descent method-based algorithm to obtain a sub-optimal reflect beamforming solution. Next, we analyze the asymptotic channel capacities by considering two types of asymptotics with respect to the transmit power and the numbers of antennas and reflecting elements. Finally, we analyze the power scaling law and the energy efficiency. By comparing the performance of our proposed algorithm with the upper bound on the performance of global optimal reflect beamforming solution, the simulation results demonstrate that our proposed algorithm can offer an outstanding performance with low computational complexity. The simulation results also show that there is no need to cost a lot on expensive antennas to achieve both high spectral efficiency and energy efficiency when the communication system is assisted by an IRS and suffer from hardware impairments.

研究动机与目标

• 解决智能反射面（IRS）辅助无线通信系统中硬件非理想性带来的挑战。
• 设计对实际硬件非理想性具有鲁棒性的发射波束成形与反射波束成形方案。
• 从频谱效率、能量效率和容量扩展规律的角度评估系统性能。
• 在实际硬件约束下分析功率扩展规律与能量效率。
• 证明即使不依赖昂贵的高精度硬件组件，也能实现高性能。

提出的方法

• 在硬件非理想条件下，采用线性最小均方误差（LMMSE）估计方法以准确获取信道状态信息。
• 在硬件非理想约束下推导出最优发射波束成形向量。
• 提出一种基于梯度下降的算法，以计算次优的反射波束成形解。
• 分析在两种情形下的渐近信道容量：高发射功率和大量天线/反射单元。
• 推导功率扩展规律，并在存在硬件非理想性的情况下评估能量效率。
• 将所提算法的性能与全局最优反射波束成形的理论上限进行对比。

实验结果

研究问题

• RQ1 硬件非理想性如何影响 IRS 辅助无线系统中波束成形的设计与性能？
• RQ2 硬件非理想性对信道估计精度和系统容量有何影响？
• RQ3 在硬件非理想条件下，低复杂度波束成形算法能否实现接近最优的性能？
• RQ4 在硬件非理想条件下，频谱效率和能量效率如何随发射功率和系统规模变化？
• RQ5 是否可能在不依赖高精度、昂贵硬件组件的情况下，实现高谱效率和能量效率？

主要发现

• 所提出的基于梯度下降的反射波束成形算法在计算复杂度显著降低的情况下，性能接近全局最优解。
• 硬件非理想性会降低系统性能，但通过合理设计波束成形，仍可实现高谱效率。
• 渐近分析表明，系统容量随发射功率提升和天线/反射单元数量增加而提高。
• 功率扩展规律表明，当使用 IRS 时，即使发射功率降低，也能维持较高的谱效率。
• IRS 的部署可提升能量效率，且在实际非理想硬件条件下，无需昂贵硬件即可实现高性能。
• 仿真结果证实，在 IRS 辅助系统中，实现高谱效率和能量效率并不需要昂贵的高精度硬件。