Channel Estimation and Power Scaling of Reconfigurable Intelligent Surface with Non-Ideal Hardware

Reconfigurable intelligent surface (RIS) technology can significantly improve the energy and spectrum efficiency of wireless communication systems. Most existing studies were conducted with an assumption of ideal hardware, while the impact of hardware impairments receives little attention. However, the non-negligible hardware impairments should be taken into consideration when we evaluate the system performance. In this paper, we consider an RIS assisted communication system with hardware impairments, and focus on the channel estimation study and the power scaling law analysis. First, with linear minimum mean square error estimation, we theoretically characterize the relationship between channel estimation performance and impairment level, number of reflecting elements, and pilot power. After that, we analyze the power scaling law and reveal that if the base station (BS) has perfect channel state information, the transmit power of user can be made inversely proportional to the BS antenna number and the square of the reflecting element number with no reduction in performance; If the BS has imperfectly estimated channel state information, to achieve the same performance, the transmit power of user can be made inversely proportional to the square-root of the BS antenna number and the square of the reflecting element number.