In this article, we study a reconfigurable intelligent surfaces (RISs)-assisted Terahertz (THz) wireless systems with hardware impairments, where <tex-math notation="LaTeX">α \!-\!μ </tex-math> small-scale fading is considered for THz links in accordance with a recent measurement campaign. First, we propose an accurate closed-form approximation of a weighted sum of cascaded nonidentical <tex-math notation="LaTeX">α \!-\!μ </tex-math> variates based on the Gauss-Laguerre quadrature and a moment-matching method. This approximate approach facilitates analysis of the RIS-THz system over <tex-math notation="LaTeX">α \!-\!μ </tex-math> fading channels. To demonstrate, we derived closed-form expressions of the outage probability (OP), the ergodic capacity (EC), and the energy efficiency (EE) of the system based on the proposed approximation. Second, we approximately characterize the end-to-end channel of the RIS-THz system when the number of RIS elements is large in scenarios with or without the presence of phase-shift errors. Based on this statistical characterization, the closed-form expressions of the OP, the EC, and the EE of the large-size RIS-THz system are obtained. Furthermore, we devise a low-complexity algorithm that jointly optimizes the transmit power and RIS element activation (i.e., ON/OFF RIS) to maximize the EE in the RIS-THz systems. This algorithm adopts an iterative dynamic programming approach for a maximum subarray problem (i.e., Kadane’s algorithm). Finally, simulations are provided to validate the accuracy of the theoretical analysis as well as demonstrate the efficacy of the devised algorithm.
No takes yet. Share an insight, caveat, or question.
Le et al. (2023) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: