  To cope with the unprecedented surge in demand for data computing for the
applications, the promising concept of multi-access edge computing (MEC) has
been proposed to enable the network edges to provide closer data processing for
mobile devices (MDs). Since enormous workloads need to be migrated, and MDs
always remain resource-constrained, data offloading from devices to the MEC
server will inevitably require more efficient transmission designs. The
integration of nonorthogonal multiple access (NOMA) technique with MEC has been
shown to provide applications with lower latency and higher energy efficiency.
However, existing designs of this type have mainly focused on the transmission
technique, which is still insufficient. To further advance offloading
performance, in this work, we propose an application-driven NOMA enabled
computation offloading scheme by exploring the characteristics of applications,
where the common data of the application is offloaded through multi-device
cooperation. Under the premise of successfully offloading the common data, we
formulate the problem as the maximization of individual offloading throughput,
where the time allocation and power control are jointly optimized. By using the
successive convex approximation (SCA) method, the formulated problem can be
iteratively solved. Simulation results demonstrate the convergence of our
method and the effectiveness of the proposed scheme.
