ROSE: Robustly Safe Charging for Wireless Power Transfer
Haipeng Dai, Yun Xu, Guihai Chen, Wanchun Dou, Chen Tian, Xiaobing Wu, Tian He
Abstract
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 does not exceed a threshold <inline-formula><tex-math notation="LaTeX">$R_t$</tex-math></inline-formula> . Nevertheless, they overlook the EMR jitter that leads to exceeding of <inline-formula><tex-math notation="LaTeX">$R_t$</tex-math></inline-formula> even if the expected EMR is no more than <inline-formula><tex-math notation="LaTeX">$R_t$</tex-math></inline-formula> . This paper studies the fundamental problem of <u>RO</u> bustly <u>S</u> af <u>E</u> 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 does not exceed <inline-formula><tex-math notation="LaTeX">$R_t$</tex-math></inline-formula> 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. After that, we propose the first redundant second-order cone constraints reduction algorithm to reduce the computational cost, and therefore obtain a <inline-formula><tex-math notation="LaTeX">$(1-\epsilon)$</tex-math></inline-formula> -approximation centralized algorithm. Further, we propose a <inline-formula><tex-math notation="LaTeX">$(1-\epsilon)$</tex-math></inline-formula> -approximation fully distributed algorithm scalable with network size for ROSE. We conduct both simulation and field experiments, and the results show that our algorithms can outperform comparison algorithms by 480.19 percent.