Power-saving method improves drone tracking under uncertain blockages
Outage-Aware Robust Sensing for UAV ISAC Systems
Information Theory
Summary
Tracking drones using signals from multiple base stations is difficult when signals get blocked unpredictably. The authors propose a way to predict which signals will be available next and focus power on the most likely useful signals instead of all possibilities. This method avoids wasting power on unlikely signal blockages and handles total signal loss separately. In tests, their approach reduced power use by nearly half while keeping tracking reliable almost all the time.
What this means in practice
- •For drone communication teams: Optimize power use for drone tracking systems when signal blockages vary dynamically to improve efficiency without losing reliability.
- •For wireless network operators: Manage multi-base-station signal resources for aerial vehicles more efficiently by predicting and adapting to likely outages.
Authors
Qiming Li, Lei Zhang, Haoran Xu, Lina Mohjazi
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.