Joint Task Offloading and Resource Allocation for NOMA-Enabled Multi-Access Mobile Edge Computing

Abstract

Multi-Access mobile edge computing (MEC) allows each user to offload partial task bits to multiple MEC servers via multi-Access radio transmission, enabling the collaboration of edge computing. By leveraging the advantage of nonorthogonal multiple access (NOMA) in improving the transmission efficiency, it is expected to effectively reduce the energy consumption of users in multi-Access MEC with the aid of NOMA. However, considering the co-channel interference of NOMA and computation collaboration among MEC servers, the joint task offloading and resource allocation is a challenging problem. In this article, with the objective to minimize the weighted sum energy of users, we first propose optimal task offloading and resource allocation algorithms for the special single-user (OTORA-SU) and general multi-user (OTORA-MU) cases, by exploiting the convex and layered structure of the formulated problem. Interestingly, it is found that the single user always preferentially offloads task bits to the MEC servers with better channel gains, regardless of the computation capacity of each MEC server. Then, a low-complexity algorithm (LTORA-MU) is proposed for the general multi-user case, which converges fast and achieves near-optimal performances. Considering the channel estimation error, the impacts of imperfect channel state information (CSI) and successive interference cancellation (SIC) are also investigated. Simulation results demonstrate that for both perfect and imperfect CSI and SIC, 1) the proposed OTORA-SU and LTORA-MU outperform the local computing, full offloading, FDMA-based offloading and non-collaborative MEC schemes; 2) as the number of MEC servers grows, the ratio of offloading task bits increases while the energy consumption is decreased.