Mobility-Aware Computation Offloading and Resource Allocation for NOMA MEC in Vehicular Networks

In vehicular networks, mobile edge computing (MEC) is emerging as a promising paradigm to provide computation services to vehicle terminals (VTs) by allowing VTs to offload computation tasks to edge servers in proximity. However, VT mobility affects both the number of VTs and their sojourn time within a given area, and brings about great uncertainty in MEC latency performance. During VT movement, offloading computation tasks to edge servers can efficiently reduce the task completion latency, and may also cause task loss due to the limited sojourn time. In this paper, we investigate mobility-aware computation offloading, and communication and computation resource allocation for nonorthogonal multiple access (NOMA) MEC in vehicular networks. Specifically, an average task completion latency minimization problem is formulated and decomposed into two tractable sub-problems, i.e., general multicarrier NOMA communication resource allocation, and joint computation offloading and computation resource allocation, which are solved by employing the convex optimization theory. All VTs are classified into two categories according to whether the sojourn time constraint can be satisfied, and an algorithm is proposed to implement computation offloading and resource allocation for different categories of VTs. Numerical results demonstrate that the proposed algorithm outperforms benchmark schemes in terms of latency performance, and VT mobility has significant impact on task completion latency.