Statistical Modeling of the Battery Recharging Time in RF Energy Harvesting for IoT Applications

Radiofrequency waves are increasingly seen as a promising solution for powering Wireless Sensor Nodes (WSN) dedicated to the Internet of Things (IoT) applications. However, by considering the RF source as a WSN power solution, Battery Recharging Time (BRT) becomes a critical performance metric, especially when the Quality of Service (QoS) is a requirement. In the literature, very few works propose an analysis of BRT based on an RF Energy Harvesting system. In this paper, the characterization of the BRT as a function of the harvestable power is analyzed, and modeling of the BRT is then proposed. The results are based on the ambient power density level measured in a building. It is obtained that the BRT undergoes as the received ambient power, a large scale fading effect shadowing more specifically the lognormal Shadowing.