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Uncertainty-guided sensing can reduce channel knowledge prediction errors by over 40% while adapting to new environments with minimal data.
Proactive beam and rate adaptation can boost effective communication rates by over 5% in dynamic urban environments, addressing critical challenges in ISAC networks.
Stop guessing where to sample next: this method uses uncertainty estimates to actively select measurements, dramatically improving radio map reconstruction from sparse data.
