Abstract
Satellite-integrated Internet is capable of providing extensive coverage for massive terrestrial sensing user equipment (UE), facilitating access that satisfies the diverse requirements of multi-type services. However, existing proactive multiple access schemes often induce severe UE collisions, particularly hindering the performance of services with stringent requirements, and thus degrading overall system utility. In this paper, we investigate a utility-oriented satellite-queried system, where rate-splitting multiple access (RSMA) is adopted to support multi-type services with utility guarantees. The utility characteristic is captured by a semantic-empowered metric, termed utility loss of information (UoI), which comprehensively integrates timeliness, service priority, transceiver matching status, and energy consumption. To minimize the average UoI, we propose an adaptive RSMA (A-RSMA) scheme that dynamically adjusts the number of sub-data and power allocation according to the number of accessing UEs. To further improve UoI, we propose an adaptive grouped RSMA (Ag-RSMA) scheme, where the covered UEs are grouped according to their diverse utility requirements. We also introduce a reinforcement learning approach to optimize the dynamic resource scheduling. Simulation results demonstrate that our A-RSMA scheme achieves a lower UoI compared to the state-of-the-art schemes, and the Ag-RSMA scheme satisfies diverse UoI requirements than its non-grouped counterpart.
| Original language | English |
|---|---|
| Pages (from-to) | 4866-4880 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Communications |
| Volume | 74 |
| DOIs | |
| State | Published - 2026 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Satellite-integrated Internet
- adaptive rate splitting multiple access
- multi-type services
- reinforcement learning
- utility loss of information
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