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HELENA for 5G NR LEO NTN Channel Estimation: A Comparative Evaluation

arXiv · AI, language, vision and robotics · article · Sep 13, 2026 · UTC

Deep Learning (DL)-based channel estimation has shown high accuracy and low latency in terrestrial 5G NR, but Low Earth Orbit (LEO) Non-Terrestrial Networks (NTNs) introduce Doppler and synchronization impairments that may require NTN-specific architectures. We test whether High-Efficiency Learning-based channel Estimation using dual Neural Attention (HELENA), originally designed for terrestrial channels, remains effective after NTN retraining and suitable across high-performance and power-constrained inference platforms. Its unchanged architecture is trained on paired receiver-compensated (NT

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First collected: 2026-09-20T12:21:05.240Z. This is not the publication date.