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Freshness-Aware Constrained Sensing-Aided Beam Prediction with Knowledge Distillation
Beam prediction leveraging environmental data reduces over-the-air beam training overhead. Existing frameworks, however, assume continuous access to fresh sensory data, an assumption that breaks down under sensing budget constraints or sensor failures. To make this more practical, this paper propose
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