Energy efficient computation offloading for nonorthogonal multiple access assisted mobile edge computing with energy harvesting devices

摘要

The mobile edge computing (MEC) is combined with wireless energy transfer (WET) to enhance the performance of wireless devices in Internet of Things (IoT) systems, which is called wireless powered mobile edge computing (WP-MEC). The sustainable energy supply and adequate computing capabilities are provided for wireless devices in WP-MEC. In this paper, we propose an online energy consumption minimization (OECM) algorithm for multiple IoT devices with latency constraints in WP-MEC environment. The nonorthogonal multiple access (NOMA) technique is used to address the preamble collision where two or more devices may select the same preamble. Based on Lyapunov optimization framework, optimal results of the time allocation for energy transfer and data transmission, the proportions of offloading tasks, data transmit powers and CPU-cycle frequencies are achieved in each time block by an iterative algorithm which leverages a convex approximation approach. The theoretical performance analysis shows that there is an upper bound of the system energy consumption. Simulation results verify that our proposed OECM algorithm outperforms the scheme without wireless energy transfer and other benchmark algorithms. (C) 2019 Elsevier B.V. All rights reserved.