Integrating Multiple RIS for Enhanced SWIPT-IoT Performance: Optimization Strategies

Abstract

Reconfigurable Intelligent Surfaces (RIS) are revolutionizing wireless communications by enhancing signal quality and extending network coverage, particularly in remotely located Internet-of-Things (IoT) applications. However, integrating multiple RIS units into Simultaneous Wireless Information and Power Transfer (SWIPT) systems presents optimization challenges for energy harvesting and data transfer. This paper aims to optimize the performance of RIS-assisted SWIPT-IoT systems, focusing on maximizing three distinct objectives of data rate, energy harvesting (EH) and energy efficiency (EE), under Time-Switching (TS) and Power-Splitting (PS) protocols. The Karush-Kuhn-Tucker (KKT) conditions, alternating optimization-based algorithm and fractional programming based Dinkelbach Transform is proposed to jointly optimize the TS/PS ratio and transmit power. Numerical simulations are conducted to evaluate system performance highlight rate-energy trade-off across different scenarios, considering factors such as RIS angular placement, surfaces count, element count, separation distance, EH and data rate demands. Additionally, the imperfect Channel State Information (CSI) has been analyzed for the proposed algorithm. These findings offer practical insights into deploying multiple RIS units for enhanced SWIPT-IoT performance in real-world settings.

Keywords

• Energy-harvesting (EH)
• Internet of Things (IoT)
• multi-RIS
• power-splitting (PS)
• reconfigurable intelligent surfaces (RIS)
• simultaneous wireless information and power transfer (SWIPT)