Robust Energy Efficiency Optimization for Double-RIS-Assisted Wireless-Powered Backscatter Communications

To explore the potential of multiple collaborative reconfigurable intelligent surfaces (RISs) for wireless-powered backscatter communications (WP-BackCom), in this paper, we investigate a robust energy efficiency (EE) optimization problem for a double-RIS-assisted WP-BackCom system, where a power station (PS) transmits wireless energy signals to multiple backscatter devices (BDs) via one RIS during the energy-harvesting phase, and then all BDs use the harvested energy for active transmission via another RIS. The total EE of all BDs with bounded channel uncertainties is maximized by jointly optimizing the beamforming vectors of the PS and RISs, transmission power, reflection coefficients, and time allocation factors. To solve the challenging problem, an iterative robust resource allocation algorithm is designed by employing the alteration optimization approach, the worst-case approach, the penalty function method, and the Gaussian randomization method. Simulation results verify that the proposed algorithm has strong robustness and higher EE.