Spatio-Temporal Semantic Inference for Resilient 6G HRLLC in the Low-Altitude Economy
This work addresses connectivity issues for autonomous aerial agents in the Low-Altitude Economy, offering incremental improvements in resilience for 6G HRLLC.
The paper tackles the problem of unreliable communication for autonomous aerial agents in 6G networks by introducing the EPIC framework, which reduces end-to-end reaction latency by 93.5% on average and maintains a deterministic 10 ms execution heartbeat despite network delays.
The rapid expansion of the Low-Altitude Economy (LAE) necessitates highly reliable coordination among autonomous aerial agents (AAAs). Traditional reactive communication paradigms in 6G networks are increasingly susceptible to stochastic network jitter and intermittent signaling silence, especially within complex urban canyon environments. To address this connectivity gap, this paper introduces the Embodied Proactive Inference for Coordination (EPIC) framework, featuring a Spatio-Temporal Semantic Inference (STSI) operator designed to decouple the coordination loop from physical signaling fluctuations. By projecting stale peer observations into a proactive belief manifold, EPIC maintains a deterministic reaction latency regardless of the network state. Extensive simulations demonstrate that EPIC achieves an average 93.5% reduction in end-to-end reaction latency, masking physical transmission delays of 150 ms with a deterministic 10 ms execution heartbeat. Crucially, EPIC exhibits strategic immunity to escalating network jitter up to 100 ms and improves the Weighted Coverage Efficiency (WCE) by 10.5% during extreme signaling silence lasting up to 50 s. These results provide the deterministic resilience essential for 6G Hyper-Reliable and Low-Latency Communication (HRLLC).