LAUSR

Nonorthogonal multiple access (NOMA) and mobile edge computing (MEC) have been emerging as promising techniques in narrowband Internet of Things (NB-IoT) systems to provide ubiquitously connected IoT devices with efficient transmission and computation. However, the successive interference cancellation (SIC) ordering of NOMA has become the bottleneck limiting the performance improvement for the uplink transmission, which is the dominant traffic flow of NB-IoT communications. Also, in order to guarantee the fairness of task execution latency across NB-IoT devices, the computation resource of MEC units has to be fairly allocated to tasks from IoT devices according to the task size. For these reasons, we investigate the joint optimization of SIC ordering and computation resource allocation in this paper. Specifically, we formulate a combinatorial optimization problem with the objective to minimize the maximum task execution latency required per task bit across NB-IoT devices under the limitation of computation resource. We prove the NP-hardness of this joint optimization problem. To tackle this challenging problem, we first propose an optimal algorithm to obtain the optimal SIC ordering and computation resource allocation in two stages: the convex computation resource allocation optimization followed by the combinatorial SIC ordering optimization. To reduce the computational complexity, we design an efficient heuristic algorithm for the SIC ordering optimization. As a good feature, the proposed low-complexity algorithm suffers a negligible performance degradation in comparison with the optimal algorithm. Simulation results demonstrate the benefits of NOMA in reducing the task execution latency.