Reconfigurable intelligent surface (RIS) can effectively control the wavefront of the impinging signals and has emerged as a cost-effective promising solution to improve the spectrum and energy efficiency of wireless systems. Most existing researches on RIS assume that the hardware operations are perfect. However, both physical transceiver and RIS suffer from inevitable hardware impairments in practice, which can lead to severe system performance degradation and increase the complexity of beamforming optimization. Consequently, the existing researches on RIS, including channel estimation, beamforming optimization, spectrum and energy efficiency analysis, etc., cannot directly apply to the case of hardware impairments. In this paper, by taking hardware impairments into consideration, we conduct the joint transmit and reflect beamforming optimization, and reevaluate the system performance. First, we characterize the closed-form estimators of direct and cascaded channels in both single-user and multi-user cases, and analyze the impact of hardware impairments on channel estimation accuracy. Then, the optimal transmit beamforming solution is derived, and a gradient descent method-based algorithm is also proposed to optimize the reflect beamforming. Moreover, we analyze the three types of asymptotic channel capacities with respect to the transmit power, the antenna number, and the reflecting element number. Finally, in terms of the system energy consumption, we analyze the power scaling law and the energy efficiency. Our experimental results also reveal an encouraging phenomenon that the RIS-assisted wireless system with massive reflecting elements can achieve both high spectrum and energy efficiency without the need for massive antennas and without allocating too many resources to optimize the reflect beamforming.
翻译:重新配置的智能表面(RIS)能够有效控制阻塞信号的波端,并已成为提高无线系统的频谱和能源效率的具有成本效益的有希望的解决方案。关于RIS的大多数现有研究认为,硬件操作是完美的;然而,物理收发器和RIS实际上都不可避免地受到硬件损坏,这可能导致系统性能严重退化,并增加光化优化的复杂程度。因此,关于RIS的现有研究,包括频道估计、波形优化、频谱和能源效率分析等,不能直接适用于硬件损坏的情况。在本文件中,通过考虑硬件损坏,我们进行联合传输并反映波形优化,并重新评估系统性能。首先,我们在单一用户和多用户案例中对直接和升级渠道的封闭式估计性估算,分析硬件损坏对频道估计准确性的影响。然后,最佳传输是模拟式的,基于梯度的计算方法算法也提议在不优化反映系统性能要素的情况下,通过不考虑硬件损坏的优化系统性能优化能量优化,最后,我们用电路段的频率分析,我们用三种类型来反映电流结构的能量结构,最后分析,我们用三个的能量结构来反映数据,然后分析我们用电流的频率分析,然后分析,我们用电流的频率分析,然后分析,我们用电流分析,用电流分析,用电流分析,用电流的频率分析,然后用电流分析,用电流分析所有电流的频率分析,用电流分析,用电压的频率分析,以优化的频率分析,然后分析,然后分析,不反映系统显示的频率分析,然后分析,用法分析,用量的频率分析,以最压的频率分析,不反映系统反映系统显示的频率分析,以优化的频率分析,以最的频率分析,再分析,再分析,再分析,再分析,我们的频率分析,再分析,再分析,再分析,然后分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,然后分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,再分析,