Reconfigurable Intelligent Surfaces with adaptive transmit power and Energy Harvesting from Vibrations
摘要
This paper investigates a Reconfigurable Intelligent Surface (RIS)-assisted underlay cognitive radio network, where a secondary transmitter harvests energy from ambient vibrations and communicates via a RIS to a secondary receiver. The transmitter adapts its power to ensure that the interference at the primary destination remains below a predefined threshold. The main objective is to optimize the secondary system throughput by determining the optimal energy harvesting duration under interference and energy causality constraints. The proposed framework analyzes both perfect and imperfect Channel State Information (CSI) scenarios, where channel estimation error is modeled using a correlation coefficient. Simulation results reveal that the throughput is maximized at an optimal harvesting duration, and RIS significantly enhances performance even in the presence of imperfect CSI. Additionally, the impact of interference from the primary user is evaluated, demonstrating that careful power adaptation and RIS configuration can sustain reliable communication in spectrum-sharing environments.