Computation Efficiency in a Wireless-Powered Mobile Edge Computing Network with NOMA

Energy-efficient computation is of crucial importance in mobile edge computing (MEC) networks. However, few investigations have studied resource allocation strategies for maximizing the computation efficiency. A computation efficiency maximization framework is established in wireless-powered MEC networks relying on non-orthogonal multiple access (NOMA) under both partial and binary computation offloading modes. A practical non-linear energy harvesting model is considered. The energy harvesting time, the local computing frequency, the operation mode selection, the offloading time and power are all jointly optimized to maximize the computation efficiency under the max-min fairness criterion. An iterative algorithm and an alternative optimization algorithm are proposed to solve the formulated challenging non-convex problems. Simulation results show that our proposed resource allocation schemes outperform the benchmark schemes in terms of computation efficiency. Moreover, a tradeoff is elucidated between the computation efficiency and the computation throughput.