Wireless-powered Multi-access Edge Computing with Cascaded zeRISs

Abstract

In this paper, we develop an energy minimization framework for wireless-powered multi-access edge computing (WP-MEC) networks, where two zero-energy reconfigurable intelligent surfaces (zeRISs) are employed to support energy harvesting and task offloading. In the downlink energy harvesting period, the hybrid access point (HAP) provides energy beamforming for multiple zero-energy devices and two zeRISs, where the harvested energy is used to offload tasks in the uplink period. Specifically, an optimization problem is formulated to minimize the energy consumption at the HAP, jointly considering the nonlinear energy harvesting model and cascaded RIS link. Next, an efficient iterative solution is designed to realize joint time allocation, HAP energy beamforming, and reflection coefficients for two-RIS by employing alternating optimization and semidefinite relaxation methods. Numerical results demonstrate the superiority of the algorithm. Compared to the corresponding single RIS setup, the energy consumption of HAP under the proposed two-zeRIS scheme is significantly reduced.