Energy-Efficient Cooperative Communication and Computation for Wireless Powered Mobile-Edge Computing

In this article, we present a wireless powered mobile-edge computing system consisting of a hybrid access point and multiple cooperative fogs, where the users in each cooperative fog can share communication and computation resources to improve their computation performance. Based on the classic time-division-multiple-access protocol, we propose a harvest-and-offload protocol to jointly schedule wireless energy transfer and cooperative computation offloading. We minimize the total energy consumption of the system by jointly considering energy beamforming, time-slot assignment, computation-task allocation, and the optimization of central processing unit (CPU) frequencies for computing. We transform the original nonconvex problem to a convex model via utilizing the variable substitution and the semidefinite relaxation methods, and then derive the optimal solution in a semiclosed form via exploiting the Lagrangian method. The extensive numerical results show that the proposed joint communication and computation cooperation scheme can reduce the total energy consumption considerably compared to the state of the art. Moreover, we demonstrate that the dynamic CPU frequency has a positive impact on energy saving compared with the case of fixed CPU frequency.