GraphJSCR uses graph representation learning to jointly decide next-hop routing, relay processing level, and semantic transmission budget in dynamic LEO satellite networks, yielding better semantic fidelity and delay tradeoffs than separate optimization baselines in simulations.
Task-oriented seman- tic delivery in large-scale heterogeneous satellite networks: A local- topological-information-dependable deep learning approach
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.NI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Joint Semantic Coding and Routing for Multi-Hop Semantic Transmission in LEO Satellite Networks
GraphJSCR uses graph representation learning to jointly decide next-hop routing, relay processing level, and semantic transmission budget in dynamic LEO satellite networks, yielding better semantic fidelity and delay tradeoffs than separate optimization baselines in simulations.