Energy-Efficient Resource Allocation for Wireless Powered Cognitive Mobile Edge Computing

In this paper, a framework for mobile edge computing (MEC) in cognitive radio (CR) networks is proposed, which integrates three technologies: MEC, cooperative relaying and wireless power transfer (WPT). The purpose of this paper is to minimize the energy cost of the WD in both partial offloading and local computing scenarios. A two-phase algorithm is proposed to solve the optimization problems. Semi-closed and closed-form solutions are derived by using Lagrangian dual decomposition and successive pseudo-convex approximation (SPCA) algorithm. Simulation results show the effects of the different parameters on the system performance and demonstrate the validity of our proposed algorithm.