Optimal Microcontroller Usage in Reconfigurable Intelligent Surface: Batteryless IoT Systems Case Study
Shakil Ahmed, Ahmed E. Kamal, Mohamed Y. Selim
TL;DR
This work tackles the challenge of powering and coordinating large RIS panels for batteryless IoT systems by introducing a Module-based control scheme. It couples non-linear energy harvesting with two-slot operation to size RIS elements into active and passive modules, each governed by a single microcontroller, and optimizes the number of modules, time slots, and BS power via iterative convexifications of a non-convex MINLP. The proposed approach yields substantial energy savings and performance gains (notably about a 100% improvement over RIS-free setups) by reducing hardware complexity and enabling scalable RIS deployment in b-IoT scenarios. The results demonstrate that RIS modules effectively boost energy harvesting and data transmission while keeping control overhead manageable, highlighting practical pathways for deploying RIS-enabled batteryless IoT networks.
Abstract
To enhance wireless communication in IoT systems using reconfigurable intelligent surfaces (RISs), efficient control of programmable passive and active elements is essential. However, increasing RIS elements requires more microcontrollers, raising complexity and cost. This paper proposes a modular approach ("Module"), where each microcontroller controls a module of optimal active or passive elements. The module size is determined using a non-linear energy harvesting model, where a batteryless IoT (b-IoT) sensor harvests energy from base station (BS) RF signals. We optimize the number of modules (microcontrollers) to minimize energy consumption while satisfying energy harvesting and information causality constraints. Simulations show that RIS module-assisted energy harvesting improves IoT system performance by ~100% compared to models without RIS panels.