Robustly Safe Charging for Wireless Power Transfer

Robustly Safe Charging for Wireless Power Transfer
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DOI：
10.1109/infocom.2018.8485951
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发表时间：
2018-04
期刊：
IEEE INFOCOM 2018 - IEEE Conference on Computer Communications
影响因子：
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通讯作者：
Haipeng Dai;Yang Zhao;Guihai Chen;Wanchun Dou;Chen Tian;Xiaobing Wu;T. He
Haipeng Dai;Yang Zhao;Guihai Chen;Wanchun Dou;Chen Tian;Xiaobing Wu;T. He
中科院分区：
其他
文献类型：
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作者：
Haipeng Dai;Yang Zhao;Guihai Chen;Wanchun Dou;Chen Tian;Xiaobing Wu;T. He

文献摘要

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无线电力传输的一个关键问题是避免电磁辐射（EMR）对人体健康造成损害。现有的研究主要集中在无线充电器的调度上，使区域内任何点的（预期）EMR不超过阈值$R_{t}$。然而，即使期望EMR不大于$R_{t}$，他们也忽略了导致Rt超过的EMR抖动。研究无线电力传输鲁棒安全充电（ROSE）的基本问题，即调度充电器的功率，使所有可充电设备的充电效用最大化，同时任何地方的EMR不超过$R_{t}$的概率不小于给定置信度。首先建立了经验概率收费模型和EMR模型。然后，我们提出EMR逼近和面积离散化技术将ROSE转化为二阶锥规划，并提出第一冗余二阶锥约束约简算法以降低计算成本，从而得到$(1-\epsilon)$-近似集中算法。此外，我们提出了一个$(1-\epsilon)$-近似全分布式算法，可随网络大小扩展。仿真和现场实验表明，我们的算法比比较算法的性能高出480.19%。
One critical issue for wireless power transfer is to avoid human health impairments caused by electromagnetic radiation (EMR) exposure. The existing studies mainly focus on scheduling wireless chargers so that (expected) EMR at any point in the area doesn't exceed a threshold $R_{t}$. Nevertheless, they overlook the EMR jitter that leads to exceeding of Rt even if the expected EMR is no more than $R_{t}$. This paper studies the fundamental problem of RObustly SafE charging for wireless power transfer (ROSE), that is, scheduling the power of chargers so that the charging utility for all rechargeable devices is maximized while the probability that EMR anywhere doesn't exceed $R_{t}$ is no less than a given confidence. We first build our empirical probabilistic charging model and EMR model. Then, we present EMR approximation and area discretization techniques to formulate ROSE into a Second-Order Cone Program, and the first redundant second-order cone constraints reduction algorithm to reduce the computational cost, and therefore obtain a $(1-\epsilon)$-approximation centralized algorithm. Further, we propose a $(1-\epsilon)$-approximation fully distributed algorithm scalable with network size for ROSE. Simulations and field experiments show that our algorithms can outperform comparison algorithms by 480.19%.