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When Wireless Charging Meets Fresnel Zones: Even Obstacles Can Enhance Charging Efficiency

机译:当无线充电符合菲涅耳区域时:甚至障碍可以增强充电效率

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Benefitting from the discovery of wireless power transfer (WPT) technology, the wireless rechargeable sensor network (WRSN) becomes a promising way for lifetime extension for wireless sensor networks. However, in practical applications, obstacles can be found almost everywhere throughout the WRSN system. Most prior arts believe that obstacles will always degrade signal strength, they omit such influences for computation simplicity, which contradicts to the instincts of signal propagation, yielding their methods unsuitable for realistic adoptions. In this paper, we explore the wireless signal propagation process and provide a theoretical charging model to enhance charging efficiency by leveraging obstacles. Through utilizing the concept of the Fresnel Zones (FZs), we re-formalize the wireless charging model and discretize charging power to determine the best charging spots as well as charging durations. We model such charging efficiency maximization with obstacles (EMO) problem as a submodular function maximization problem and propose a cost-efficient algorithm with approximation ratio (e-1)/ε (1 - ε) to solve it. Finally, test-bed experiments and simulations are conducted to verify that our schemes outperform comparison algorithms by at least 10% in charging efficiency improvement.
机译:从无线电力传输(WPT)技术的发现中受益,无线可充电传感器网络(WRSN)成为无线传感器网络的寿命扩展的有希望的方式。然而,在实际应用中,几乎可以在整个WRSN系统中找到障碍物。大多数现有技术认为,障碍会一直降低信号强度,他们忽略了简单的计算这种影响,这与对信号传播的本能,产生它们的方法不适合现实收养。在本文中,我们探讨了无线信号传播过程,并提供了一种通过利用障碍物来增强充电效率的理论充电模型。通过利用菲涅耳区域(FZS)的概念,我们重新形成无线充电模型并使充电能力分离以确定最佳充电点以及充电持续时间。我们用障碍物(EMO)问题为子骨髓函数最大化问题的这种充电效率最大化,提出了一种具有近似比(E-1)/ε(1 - ε)的成本有效的算法来解决它。最后,进行了试验床实验和模拟,以验证我们的方案优于比较算法至少10%,以提高收费效率。

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