Statistical Modeling of the Battery Recharging Time in RF Energy Harvesting for IoT Applications
Autor: | Nahi Kandil, Alex Mouapi, Nadir Hakem |
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Rok vydání: | 2020 |
Předmět: |
Battery (electricity)
Computer science business.industry Quality of service 020208 electrical & electronic engineering Electrical engineering 020206 networking & telecommunications 02 engineering and technology 0202 electrical engineering electronic engineering information engineering Wireless Fading Radio frequency Shadow mapping business Wireless sensor network Performance metric |
Zdroj: | 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting. |
DOI: | 10.1109/ieeeconf35879.2020.9330240 |
Popis: | 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. |
Databáze: | OpenAIRE |
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