A PKG-assisted RSMA scheme with joint trajectory-power-beamforming-compression optimization is developed for multi-user semantic communication in UAV networks and shown in simulations to beat conventional RSMA, NOMA, and SDMA on energy efficiency and semantic accuracy.
Transformer- based collaborative reinforcement learning for fluid antenna system (FAS)-enabled 3d UA V positioning,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Rate-Splitting Multiple Access Enabled Probabilistic Semantic Communication in UAV Networks
A PKG-assisted RSMA scheme with joint trajectory-power-beamforming-compression optimization is developed for multi-user semantic communication in UAV networks and shown in simulations to beat conventional RSMA, NOMA, and SDMA on energy efficiency and semantic accuracy.