Optimal Microcontroller Usage in Reconfigurable Intelligent Surface: Batteryless IoT Systems Case Study

TL;DR

This paper presents an optimized, modular microcontroller approach for reconfigurable intelligent surfaces in IoT systems, leveraging energy harvesting to reduce energy consumption and improve system performance.

Contribution

It introduces a modular control scheme for RIS elements based on energy harvesting models, optimizing microcontroller deployment for energy efficiency in batteryless IoT systems.

Findings

RIS module-assisted energy harvesting doubles IoT system performance

Optimized microcontroller deployment reduces energy consumption

Modular control scheme enhances RIS scalability and efficiency

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.