Joint task scheduling and uplink/downlink radio resource allocation in PD-NOMA based mobile edge computing networks

Abstract

Mobile edge computing (MEC) is a new paradigm that brings the computation capabilities closer to the edge of wireless networks. In doing so, the computation tasks of users can be offloaded to the network edge for remote executing. Since both the computing and transmission delays in uplink and downlink of each task offloading operation affect the total task execution delays, it is necessary to utilize the physical layer transmission opportunities in the task allocation algorithms. In this regard, we develop an efficient algorithm to minimize the total execution delay of users in a single-cell power-domain non-orthogonal multiple access (PD-NOMA) based MEC system with multiple users and single MEC server. Hence the computation task of each user can be partitioned into two separated parts, one for offloading to the network edge and another for locally computing. In the considered partial offloading scheme, we jointly obtain subcarrier and transmit power allocation policies for both the uplink and downlink transmissions with task scheduling and computation resource allocation at both the users and the MEC server. Numerical results demonstrate that when the communication and computation resources are jointly optimized at the task allocation algorithms, the network performance is improved nearly 30% compared to the existing joint computation and task allocation approach in which both the downlink and uplink data rates are assumed to be fixed.