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Reconfigurable intelligent surface (RIS) can effectively control thewavefront of the impinging signals and has emerged as a cost-effectivepromising solution to improve the spectrum and energy efficiency of wirelesssystems. Most existing researches on RIS assume that the hardware operationsare perfect. However, both physical transceiver and RIS suffer from inevitablehardware impairments in practice, which can lead to severe system performancedegradation and increase the complexity of beamforming optimization.Consequently, the existing researches on RIS, including channel estimation,beamforming optimization, spectrum and energy efficiency analysis, etc., cannotdirectly apply to the case of hardware impairments. In this paper, by takinghardware impairments into consideration, we conduct the joint transmit andreflect beamforming optimization, and reevaluate the system performance. First,we characterize the closed-form estimators of direct and cascaded channels inboth single-user and multi-user cases, and analyze the impact of hardwareimpairments on channel estimation accuracy. Then, the optimal transmitbeamforming solution is derived, and a gradient descent method-based algorithmis also proposed to optimize the reflect beamforming. Moreover, we analyze thethree types of asymptotic channel capacities with respect to the transmitpower, the antenna number, and the reflecting element number. Finally, in termsof the system energy consumption, we analyze the power scaling law and theenergy efficiency. Our experimental results also reveal an encouragingphenomenon that the RIS-assisted wireless system with massive reflectingelements can achieve both high spectrum and energy efficiency without the needfor massive antennas and without allocating too many resources to optimize thereflect beamforming.

Beamforming Design and Performance Evaluation for Reconfigurable Intelligent Surface Assisted Wireless Communication Systems With Non-Ideal Hardware