Joint Resource Allocations for Energy Consumption Optimization in HAPS-Aided MEC-NOMA Systems

In this paper, the energy consumption (EC) optimization of an aerial high altitude platform station (HAPS) aided mobile edge computing (MEC) network with non-orthogonal multiple access (NOMA) in the presence of imperfect successive interference cancellation is studied. Specifically, joint design schemes of the resource allocation (RA) and the two-dimensional (2D) horizontal position are proposed to minimize the sum EC subject to the different constraint conditions. In particular, we jointly optimize the receive beamforming (BF), the power allocation (PA), HAPS position, the local computation resource, the computation task offload coefficient, and the computation resource allocated for each user via the block coordinate descent method. Namely, given the other optimization parameters, we first optimize a 2D position of HAPS. Then, given the 2D position, by introducing the auxiliary variables, a joint design of BF, PA, offload coefficient and computation resource is solved by an efficient iteration algorithm based on the successive convex approximation method. Additionally, a suboptimal joint design scheme is also developed to lower the complexity. Simulation results show that the proposed two design schemes of the joint RA and position are effective in reducing the EC, and they have a lower EC when compared to benchmark schemes.