Enhanced IoT Batteryless D2D Communications Using Reconfigurable Intelligent Surfaces

Abstract

Recent research on reconfigurable intelligent surfaces (RIS) suggests that the RIS panel, containing passive elements, enhances channel performance for the internet of things (IoT) systems by reflecting transmitted signals to the receiving nodes. This paper investigates RIS panel assisted-wireless network to instigate minimal base station (BS) transmit power in the form of energy harvesting for batteryless IoT sensors to maximize bits transmission in the significant multi-path environment, such as urban areas. Batteryless IoT sensors harvest energy through the RIS panel from external sources, such as from nearby BS radio frequency (RF) signal in the first optimal time frame, for a given time frame. The bits transmission among IoT sensors, followed by a device-to-device (D2D) communications protocol, is maximized using harvested energy in the final optimal time frame. The bits transmission is at least equal to the number of bits sampled by the IoT sensor. We formulate a non-convex mixed-integer non-linear problem to maximize the number of communicating bits subject to energy harvesting from BS RF signals, RIS panel energy consumption, and required time. We propose a robust solution by presenting an iterative algorithm. We perform extensive simulation results based on the 3GPP Urban Micro channel model to validate our model.

Revolutionizing Batteryless IoT Systems to Enhance Nonlinear Energy Harvesting Using RIS Active and Passive Elements

“…Therefore, RIS panels make IoT systems energy efficient by reflecting and amplifying incident signals so that the destination nodes receive directional and stronger transmit signals. In our previous work, we completed the first exploratory studies focused on optimizing RIS active and passive elements to improve data rates and energy harvesting in b-IoT systems employing a linear energy harvesting model [8], [9]. As valuable as these fundamental works are, our current paper aims to go beyond them by exploring the nonlinear model of energy generation.…”