AI & ML
Outage-Aware Robust Sensing for UAV ISAC Systems
arXiv math.IT0 views
arXiv:2610.11720v1 Announce Type: cross Abstract: Integrated sensing and communications (ISAC) infrastructure can provide an external perception layer for aerial robots, but dynamic blockage makes the set of informative sensing links at the next update uncertain. A single predicted availability pattern can miss low-information outcomes, whereas protecting all patterns wastes power and may become infeasible when all links are blocked. We propose an outage-aware conformal robust power-allocation framework for multi-BS UAV tracking. A history-aware joint predictor maps radar and tracking histories to next-slot availability probabilities, and adaptive prediction sets retain plausible correlated patterns. Tracking constraints are enforced only for retained non-outage patterns, while the all-blocked pattern is treated separately as a physical sensing outage. With per-slot beam directions fixed, the resulting scalar-power allocation is a semidefinite program. A reliability bound relates serviceable-slot tracking failure to deployed-policy miscoverage and optimization infeasibility. Across paired closed-loop simulations over five random seeds, the method attains a 0.01% serviceable-slot constraint-violation rate and uses 47.0% less power than protection over all non-outage patterns.
Source:https://arxiv.org/abs/2610.11720PreviousMinimal Scenarios Witnessing Genuine Multipartite Nonlocality PossibilisticallyNextSAVU-BENCH: A Real-World Benchmark for Spatial Audio-Visual Understanding
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