Knowledge distillation creates a lightweight student model that reaches over 96% top-5 beam prediction accuracy on real multimodal sensor data while using 27 times fewer parameters than the teacher.
Deepsense 6G: A large-scale real-world multi-modal sensing and communication dataset ,
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Knowledge distillation creates a compact neural network for long-term beam tracking in mmWave communications that matches a larger teacher's accuracy with far fewer parameters and shorter input sequences.
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Knowledge Distillation for Lightweight Multimodal Sensing-Aided mmWave Beam Tracking
Knowledge distillation creates a lightweight student model that reaches over 96% top-5 beam prediction accuracy on real multimodal sensor data while using 27 times fewer parameters than the teacher.
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Knowledge Distillation for Sensing-Assisted Long-Term Beam Tracking in mmWave Communications
Knowledge distillation creates a compact neural network for long-term beam tracking in mmWave communications that matches a larger teacher's accuracy with far fewer parameters and shorter input sequences.