Core Concepts
Optimizing energy efficiency in SWIPT systems using active STAR-RIS technology.
Abstract
This article discusses the optimization of energy efficiency in simultaneous wireless information and power transfer (SWIPT) systems with active simultaneously transmitting and reconfigurable intelligent surfaces (STAR-RIS). The authors propose an alternating optimization solution approach to maximize energy efficiency by optimizing various parameters. The paper combines convex optimization techniques with deep reinforcement learning methods to achieve efficient resource allocation. Simulation results demonstrate the effectiveness of the proposed scheme, showing a significant improvement over passive systems.
The content is structured as follows:
Introduction to the background and motivation for SWIPT systems.
Research challenges and contributions in optimizing active STAR-RIS-assisted systems.
Formulation of an energy efficiency maximization problem.
Convexity analysis and solution strategy breakdown into sub-problems.
Detailed solutions to sub-problems using classical convex optimization methods and DRL-based algorithms.
Conclusion with simulation results and future directions.
Stats
Our simulations show the proposed system outperforms its passive counterpart by 57% on average.
Quotes
"Our simulations show the effectiveness of the proposed resource allocation scheme."
"Simulation results show that our proposed active STAR-RIS-based SWIPT scheme achieves a significant system EE gain of around 57%."