Energy-Sensitive Binary Offloading for Reconfigurable-Intelligent-Surface-Assisted Wireless-Powered Mobile-Edge Computing
Yizhen Yang, Yi Gong, Yik‐Chung Wu
Abstract
Wireless power transfer (WPT) is recognized as a promising technique to alleviate the energy limitation of wireless devices (WDs) under mobile-edge computing (MEC) scenario in the upcoming Internet of Things (IoT) era. In wireless-powered MEC networks, WDs can utilize the harvested energy to handle the computation tasks. Furthermore, reconfigurable intelligent surface (RIS) can also play a significant role in MEC systems due to its capability to enhance the channel quality. In this article, we investigate an RIS-assisted wireless-powered MEC system where each WD follows the binary offloading policy. The objective is to minimize the total energy consumption of WDs by jointly optimizing the WPT time, the RIS phase shifts for WPT, the binary mode selection, the CPU frequencies for local computation, the RIS phase shifts for offloading, and the offloading times and powers. A gradient ascent-based algorithm with linear complexity with respect to the number of RIS reflecting elements is proposed to optimize the transmit power and RIS phases shifts design. On the other hand, a penalty-based algorithm with linear complexity with respect to the number of WDs is proposed to solve the offloading decision and time allocation. Numerical results are presented to demonstrate the effectiveness of the proposed system and algorithms.