With an increasing number of IoT devices deployed to many applications such as retail, healthcare, transportation, and industrial automation, the power supply of these IoT devices is becoming a critical problem. Because it is impractical to replace or recharge the battery of the mass IoT devices, which labor-intensive and time-consuming. Though we can provide power for the IoT devices by extracting vibration energy, thermal energy, and solar energy, RF energy has the advantages of fewer placement constraints and existing free RF resources, which makes it a promising solution for powering IoT devices.

The key problems of RF energy harvesting are the low power density of the ambient RF environment and its time-changing characteristic, which limit the harvested power and result in low powe...[ Read more ]

With an increasing number of IoT devices deployed to many applications such as retail, healthcare, transportation, and industrial automation, the power supply of these IoT devices is becoming a critical problem. Because it is impractical to replace or recharge the battery of the mass IoT devices, which labor-intensive and time-consuming. Though we can provide power for the IoT devices by extracting vibration energy, thermal energy, and solar energy, RF energy has the advantages of fewer placement constraints and existing free RF resources, which makes it a promising solution for powering IoT devices.

The key problems of RF energy harvesting are the low power density of the ambient RF environment and its time-changing characteristic, which limit the harvested power and result in low power conversion efficiency. In this thesis, the system level of RF energy harvesting is investigated to address the challenging problems and extract as much energy from the ambient RF environment as possible.

Firstly, the analytical model of a differential-drive cross-coupled rectifier and optimization procedures for the most power-efficient rectifiers are provided, which achieve high power conversion efficiency and high sensitivity. Secondly, the design and analysis of a compact dual-wideband multi-mode resonant printed quasi-Yagi antenna with a dual-driven element are presented, which has a small size and wide bandwidth. Thirdly, a statistical model based on kernel density estimation and a prediction method based on the moving average for the power density of mobile service channels are derived, which matches well with the measurement results and enables accurate and effective prediction. Fourthly, a compact dual-band four-port ambient RF energy harvester with high sensitivity, high efficiency, and wide power range is introduced to replace the battery of mass IoT devices. Fifthly, a buck-boost converter that is event-driven multi-input multi-output with adaptive maximum power point tracking is proposed, which achieves high power conversion efficiency and a wide input power range.