A greedy algorithm with swap and a transformer model trained by imitation and reinforcement learning achieve higher spectral efficiency than prior methods for port selection in fluid antenna multiple access at practical complexity.
Slow fluid antenna multiple access,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Greedy and Transformer-Based Multi-Port Selection for Slow Fluid Antenna Multiple Access
A greedy algorithm with swap and a transformer model trained by imitation and reinforcement learning achieve higher spectral efficiency than prior methods for port selection in fluid antenna multiple access at practical complexity.