Maximizing Charging Efficiency With Fresnel Zones

IEEE TRANSACTIONS ON MOBILE COMPUTING(2024)

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摘要
Benefitting from the discovery of wireless power transfer (WPT) technology, the wireless rechargeable sensor network (WRSN) has become a promising way for lifetime extension for wireless sensor networks. In practical WRSN scenarios, obstacles can be found almost everywhere. Most state-of-the-art researches believe that obstacles will always degrade signal strength, and omit the influence of obstacles for simplifying the computation process. However, overlooking the positive impacts of obstacles on signal propagation is inconsistent with the intrinsic features of electromagnetic waves. To address this issue, in this paper, we explore the wireless signal propagation process and provide a theoretical charging model to enhance the charging efficiency by leveraging obstacles. Through utilizing the concept of the Fresnel Zone model, we re-formalize the wireless charging model and discretize the charging area and charging time to determine the best charging locations as well as charging duration. We model the charging Efficiency Maximization with Obstacles (EMO) problem as a submodular function maximization problem and propose a cost-efficient algorithm to solve it. Finally, test-bed experiments and extensive simulations are both conducted to verify that our schemes outperform baseline algorithms by $33.46\%$33.46% on average in charging efficiency improvement.
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关键词
Wireless sensor networks,Costs,Wireless communication,Mathematical models,Mobile computing,Fresnel reflection,Inductive charging,Wireless rechargeable sensor networks,Fresnel Zones,charging energy maximization,submodular function maximization
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