QuaMoE-DRF forecasts dynamic beam-SINR fields to enable proactive BS, beam, and MCS decisions in ISAC networks, reporting 402.5 Mbps effective rate and 0.0417 outage on a simulated multi-BS urban benchmark.
JSR-GFNet: Jamming-to-Signal Ratio-Aware Dynamic Gating for Interference Classification in future Cognitive Global Navigation Satellite Systems
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
GeoUQ-GFNet reconstructs dense urban gain radio maps from sparse measurements using geometry priors and uncertainty-guided active sensing, showing consistent gains over non-adaptive sampling on the new UrbanRT-RM ray-tracing benchmark.
FPN-Transformer with uncertainty head reduces RMSE for cross-height CKM prediction to 5.347 dB zero-shot and 3.518 dB few-shot on a layered aerial benchmark, outperforming 3D-RadioDiff.
citing papers explorer
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QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks
QuaMoE-DRF forecasts dynamic beam-SINR fields to enable proactive BS, beam, and MCS decisions in ISAC networks, reporting 402.5 Mbps effective rate and 0.0417 outage on a simulated multi-BS urban benchmark.
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Sparse Gain Radio Map Reconstruction With Geometry Priors and Uncertainty-Guided Measurement Selection
GeoUQ-GFNet reconstructs dense urban gain radio maps from sparse measurements using geometry priors and uncertainty-guided active sensing, showing consistent gains over non-adaptive sampling on the new UrbanRT-RM ray-tracing benchmark.
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Geometry-Aware Cross-Height Channel Knowledge Map Prediction for UAV-Assisted Communications With Uncertainty-Guided 3D Sensing
FPN-Transformer with uncertainty head reduces RMSE for cross-height CKM prediction to 5.347 dB zero-shot and 3.518 dB few-shot on a layered aerial benchmark, outperforming 3D-RadioDiff.