Reconfigurable Intelligent Surface aided Wireless Powered Mobile Edge Computing

Yidong Lu, Jun Zhao

Abstract: Wireless powered mobile edge computing (WPMEC) has been proposed to fulfill the computational energy requirements of massive power-constrained Internet-of-Things (IoT) devices. However, the transmission rate for task offloading and the efficiency of energy transfer are compromised when the wireless connections between the mobile devices and hybrid access point (HAP) are hostile. We proposed to employ the reconfigurable intelligent surface (RIS), an emerging technology that is capable of enhancing wireless connections. Specifically, we consider optimizing a weighted sum of energy and time while guaranteeing the energy harvested from the wireless power transfer (WPT) stage can cover the energy consumption of each mobile device and maintain each device a customized transmission rate to increase the edge server's earning maximally. First, we proposed a RIS-aided wireless powered MEC system design and introduced the earning of the edge server as the metric to evaluate the performance of the system. Then we formulated an optimization problem and proposed an iterative algorithm to maximize the earning received by the edge server. Finally, our numerical results show that RIS can significantly reduce the time and energy cost of the WP-MEC system.