Optimization-oriented modeling and analysis of RIS-assisted SWIPT-IOT systems

Abstract

The rapid evolution of wireless communication technologies toward beyond-5G (B5G) and sixth-generation (6G) networks has unlocked a new era of massive connectivity and intelligent automation, where billions of Internet-of-Things (IoT) devices are expected to reshape the application areas ranging from remote environmental monitoring to precision agriculture. Such areas require the self-sufficiency of IoT devices with higher data rate and energy harvesting (EH) solutions that are convenient, safe, uninterruptible and flexible. The conventional EH options like wind, solar, etc., are highly unpredictable, thus harnessing radio frequency (RF) electromagnetic (EM) waves and convert them to usable direct current (DC) serves our purpose. In this context, Simultaneous Wireless Information and Power Transmission (SWIPT) has emerged as a promising approach capable of jointly delivering information and RF energy to wireless devices, having potential to reduce the need for frequent battery replacement. When extending the coverage of SWIPT receivers, a green communication solution lies in integration of SWIPT with Reconfigurable Intelligent Surfaces (RIS) technology. RIS has gained considerable attention due to its ability to intelligently manipulate the wireless propagation environment, thereby significantly enhancing the communication reliability and energy efficiency (EE). Motivated by these advancements, this thesis presents a comprehensive investigation of RIS-assisted SWIPT systems for next-generation IoT-enabled wireless networks under practical deployment constraints.