Joint Throughput-Optimal Scheduling and Energy Efficiency Optimization for NOMA Systems With Flow-Level Dynamics

In wireless networks, scheduling becomes a necessity to dynamically match user selection and resource allocation with traffic needs and wireless channel conditions. Plenty of previous works focus on scheduling in non-orthogonal multiple access (NOMA) networks. They implicitly assume that the number of users is fixed and traffic sources keep on injecting traffic into the system. Then the optimization problems related to the energy efficiency (EE) and the spectral efficiency (SE), are investigated. However, long-lived flows and short-lived flows exist simultaneously in complex actual environments. We, for the first time, investigate a downlink NOMA system with flow-level dynamics and formulate an optimization problem of scheduling in this article. We aim to maximize the short-term EE at each time slot and simultaneously guarantee the long-term network queue stability (throughput-optimality), under the quality of service (QoS) constraints of each achievable data rate and the total of transmission powers at each time slot. Based on the Lyapunov optimization theory, the original problem is transformed into an optimization problem that independent of time, and then the optimal algorithm is proposed. Moreover, we analyze the complexity of proposed algorithm. Simulation results show that the optimal algorithm is throughput-optimal, and its performance is better than that of the benchmark algorithm in terms of EE and the scheduling delay.