Integrated Design and Performance Optimization of Receiver Circuits for Radio Frequency Energy Harvesting Applications

Radio Frequency Energy Harvesting (RFEH) has emerged as a promising solution to sustainably power the expanding ecosystem of low-power Internet of Things (IoT) devices. However, the realization of efficient RFEH systems necessitates specialized receiver circuits that can operate under ultra-low-power conditions without relying on conventional power sources. This paper presents a comprehensive analysis, design methodology and optimization framework for such circuits, targeting the dual challenges of limited ambient RF energy and stringent power constraints that preclude the use of traditional amplification techniques. We begin by systematically examining the key building blocks of RFEH receivers — namely, the antenna, Impedance Matching (IM) network and rectifier — and then conduct a critical review of existing literature to highlight gaps in practical circuit realization. A novel and streamlined design approach is introduced, enabling precise determination of circuit parameters tailored to specific load conditions — an aspect often overlooked in prior studies. Our primary contribution lies in a rigorous mathematical formulation of two-element IM networks, through which we derive closed-form expressions for optimal component values across six topologies. Furthermore, we demonstrate the infeasibility of certain configurations, such as single-inductor and specific multi-element designs, thereby challenging widely adopted but suboptimal design paradigms. The analytical results are corroborated via Advanced Design System (ADS) simulations, showing high fidelity between calculated and simulated values. Additionally, a sensitivity analysis identifies a particular topology as the most robust under parameter variations. This work distinguishes itself through a systematic, load-aware design framework and its analytical proof of structural limitations in common IM configurations. By bridging theoretical rigor with practical relevance, the proposed methodology provides a scalable foundation for the development of high-efficiency RFEH systems, advancing beyond the limitations of purely simulation-driven or overly simplified design approaches.