Lyapunov Optimization based Queue-aware Traffic Shaping for 5G-TSN in Industrial Environments

2026-06-24

AI Summary

In industrial 5G environments, metal structures induce severe signal fading, causing conventional transport protocols to suffer from delayed responsiveness, bufferbloat, and excessive latency that jeopardize safety-critical timing bounds. This work addresses these challenges by introducing, for the first time, Lyapunov drift-plus-penalty theory into cross-layer rate control for 5G-TSN integration, proposing a channel-prediction-free, queue-aware traffic shaping mechanism that dynamically balances service utility against queue stability. Simulation results based on 3GPP-compliant occlusion trajectories demonstrate that the proposed approach effectively suppresses bufferbloat, prevents catastrophic queue buildup, and achieves near-deterministic low-latency performance upon channel recovery.

Abstract

Manufacturing companies look increasingly at Private 5G networks to manage Automated Guided Vehicles (AGVs). While 5G promises Ultra-Reliable Low Latency Communication (URLLC), its service quality is challenged by industrial environments characterized by dense metallic structures, which frequently cause line-of-sight (LOS) blockage events, causing deep fades in received signal levels that can degrade channel capacity to near-zero. Standard transport protocols and rate adaptation mechanisms fail to react sufficiently fast to these deep fades, resulting in bufferbloat and latency spikes that violate safety margins. In this paper, we propose a cross-layer rate control algorithm based on Lyapunov Drift-plus-Penalty theory. The proposed controller dynamically optimizes the trade-off between service utility and queue stability based on instantaneous buffer states, without requiring predictive channel models. We validate the approach using a trace-driven simulation framework that replicates the stochastic dynamics of 5G blockage using 3GPP-compliant capacity data. Numerical results demonstrate that while baseline scheduling schemes suffer from catastrophic queue accumulation, leading to excessive delays upon reconnection, the proposed Lyapunov controller effectively eliminates bufferbloat. By preventing congestion-induced backlog, the system ensures immediate low-latency operation as soon as the channel recovers, maintaining near-deterministic behavior.

Problem

• 5G-TSN
• URLLC
• bufferbloat
• LOS blockage
• industrial environments

Innovation

• Lyapunov optimization
• queue-aware traffic shaping
• 5G-TSN
• bufferbloat mitigation
• industrial 5G