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Abstract

The proliferation of Internet of Things (IoT) devices has transformed the technological landscape by embedding smart functionalities into everyday objects. Despite these advancements, most IoT devices continue to rely on traditional batteries, which present challenges such as limited lifespan, frequent replacements, and environmental concerns due to electronic waste. Ambient IoT, a technology currently undergoing standardization, seeks to address these issues by enabling devices to operate sustainably using harvested environmental energy. However, standardization efforts have not yet fully addressed energy harvesting, leaving its practical deployment uncertain. Focusing on radio frequency (RF) energy harvesting, this work examines holistic models to evaluate the performance of energy harvesting systems within the context of Ambient IoT. By examining ongoing standardization efforts and identifying the unique design requirements of Ambient IoT devices, we illustrate how Ambient IoT differs from existing technologies. Key performance metrics, specifically energy harvesting coverage and charging probability, are introduced to assess the effectiveness of various RF energy sources. This thesis further explores the feasibility of powering Ambient IoT devices through ambient RF sources by integrating real-world measurements and generating pseudo-ambient data that represents the available power across various lo- cations. To account for the inherent variability in RF signals, an autoregressive process is employed to model the correlations between data points. The numerical results demonstrate that while ambient RF energy harvesting is viable in outdoor settings, indoor environments pose significant challenges due to low mean power densities. In addition to ambient RF sources, we examine dedicated RF energy sources to improve the reliability and coverage of power delivery for Ambient IoT devices. By strategically deploying dedicated sources using point processes related to real-world communication infrastructure and integrating multi-antenna systems, numerical results indicate significant enhancements in energy harvesting, especially in power-limited indoor environments.