Search

Age of Information (AoI) is a critical performance metric for measuring information freshness in task-oriented Internet of Things (IoT) applications. In this work, we investigate how AoI impacts task-oriented multicasting in multi-cell Non-orthogonal Multiple Access (NOMA) networks, while considering the effects of inter-cell interference and multicast group size. Our findings reveal that larger group sizes lead to increased instability in AoI, but lower inter-cell interference; while smaller group sizes result in higher inter-cell interference but a smaller increase in AoI when transmission fails. To balance inter-cell interference and group size, we propose a novel AoI-aware inter-cell interference mitigation (AIM) solution, which dynamically adjusts multicast group size, schedules multicast groups for transmission, and allocates transmit power to multicast groups. We derive the optimality for achieving the lowest AoI of the AIM scheduling strategy and the upper bound of the number of scheduling groups. Our simulation results show that AIM ensures more successful transmissions and low weighted sum AoI through grouping and AoI-aware inter-cell interference mitigation. We also show that our AoI-aware grouping scheme outperforms random grouping and fixed grouping, as well as evolutionary-based genetic algorithm grouping, by modeling the grouping problem as a multi-armed bandit problem and solving it using the $\epsilon $ -greedy method. To the best of our knowledge, this is the first study to examine the AoI problem of task-oriented IoT applications in multi-cell multicast NOMA networks.