SYSYMay 18

Control-Certified Wireless Resource Allocation for Digital-Twin-Enabled UAV Swarms

arXiv:2605.177914.7
Predicted impact top 61% in SY · last 90 daysOriginality Incremental advance
AI Analysis

For multi-hop UAV swarms requiring safe closed-loop control, this work provides a method to certify and allocate wireless resources with guaranteed control safety.

The paper introduces a certificate-guided resource allocation framework for digital-twin-enabled UAV swarms that ensures both network feasibility and control safety. In ns-3 simulations, it outperforms baselines in tracking accuracy and high-risk state suppression under identical communication budgets.

Wireless resource allocation in digital-twin-enabled unmanned aerial vehicle (UAV) swarms must be both network-feasible and certifiably safe for closed-loop control. Existing packet-level or scalar-priority schedulers cannot meaningfully compare heterogeneous multi-hop actions that differ simultaneously in route, retransmission depth, blocklength, bidirectional delay, delivery probability, and TDMA slot cost. This paper introduces a certificate-guided resource allocation framework for low-altitude multi-hop UAV swarms. A digital twin maps predicted topology, channel, route, and controller-side state into a shared five-dimensional quality-of-service (QoS) certificate comprising uplink/downlink delay bounds, directional delivery guarantees, and a certified upper bound on the interval between successful bidirectional interactions. A state-conditioned stochastic drift test then admits only certificates whose augmented Lyapunov drift is nonpositive under the current controller state. Admitted actions are reduced to certified supply frontiers by removing dominated route-slot configurations, and the online scheduler maximizes Lyapunov-drift reduction under a shared TDMA slot budget via exact dynamic programming. Closed-loop ns-3 simulations demonstrate that the proposed framework outperforms fixed-service, certificate-filtered fixed-priority, dynamic-transmission-count, and value-of-information baselines in both tracking accuracy and high-risk state suppression under identical communication budgets.

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