HELENA delivers a smaller dual-attention neural estimator that cuts inference time by 45% and parameters by 8x versus CEViT while keeping comparable NMSE accuracy.
Low complexity deep learning augmented wireless channel estimation for pilot-based ofdm on zynq system on chip,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.SP 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
HELENA: High-Efficiency Learning-based channel Estimation using dual Neural Attention
HELENA delivers a smaller dual-attention neural estimator that cuts inference time by 45% and parameters by 8x versus CEViT while keeping comparable NMSE accuracy.