Multi-objective optimization for NOMA-based mobile edge computing offloading by maximizing system utility

Mobile Edge Computing (MEC) is a technology for the fifth-generation (5G) wireless communications to enable User Equipment (UE) to offload tasks to servers deployed at the edge of network. However, taking both delay and energy consumption into consideration in the 5G MEC system is usually complex and contradictory. Non-orthogonal multiple access (NOMA) enable more UEs to offload their computing tasks to MEC servers using the same spectrum resources to enhance the spectrum efficiency for 5G, which makes the problem even more complex in the NOMA-MEC system. In this work, a system utility maximization model is present to NOMA-MEC system, and two optimization algorithms based on Newton method and greedy algorithm respectively are proposed to jointly optimize the computing resource allocation, SIC order, transmission time slot allocation, which can easily achieve a better trade-off between the delay and energy consumption. The simulation results prove that the proposed method is effective for NOMA-MEC systems.