Age-Optimal Downlink NOMA Resource Allocation for Satellite-Based IoT Network

The upcoming satellite-based Internet of Things (S-IoT) has the capability to provide timely status updates to massive terrestrial user equipments (UEs) via non-orthogonal multiple access (NOMA), due to the worldwide coverage inherited from satellite. Considering the constrained power and storage resources while keeping the information freshness in S-IoT, we first propose three constraint conditions including average/peak power constraints, network stability and minimum throughput requirement. Then, we formulate a long-term age of information (AoI) minimization problem under the three constraint conditions. To solve this complex long-term problem, we transform the above mentioned constraints into three queue stability problems via the Lyapunov optimization framework, thus converting our long-term multi-slot stochastic optimization problem into a series of single time slot deterministic optimization problems. Moreover, we leverage the ListNet algorithm to derive the weights of the queue backlog and channel conditions to obtain an optimized power allocation order with linear complexity. Finally, we utilize the particle swarm optimization algorithm to derive the NOMA long-term AoI minimization (AM) power allocation problem within a practical complexity, named NOMA-AM scheme. Simulation results show that the proposed NOMA-AM scheme has the lowest expected weighted sum AoI compared to several benchmark schemes.