5G scheduling improves delay and reliability for industrial networks
Overload-Robust Latency in 5G-TSN: A HoL-Enhanced Hybrid Lyapunov Approach for 3GPP Indoor Factory Environments
Networking and Internet Architecture
Summary
5G networks in factories must handle very different types of data, some needing super-fast and reliable delivery, others needing lots of capacity. The authors propose a new scheduling method that better manages this mix, especially when there are more devices than usual. Their approach reduces delays for critical control data and keeps it going even during heavy overloads, though with some reduction in overall throughput. This helps factory networks stay dependable when unexpected traffic spikes happen.
What this means in practice
- •For industrial network engineers: Use the proposed scheduler to improve delay and reliability for safety-critical control traffic in privately owned 5G factory networks during device overloads.
- •For wireless network operators: Implement overload-robust scheduling to prioritize critical industrial traffic under fixed spectrum and high load, reducing deadline misses compared to existing schedulers.
Authors
Kouros Zanbouri, Md Noor-A-Rahim, Cormac J Sreenan, Dirk Pesch
Abstract
Private 5G networks are a key enabler for flexible industrial automation, especially when used in conjunction with Time-Sensitive Networking (TSN) technology. In this context, radio schedulers must multiplex safety-critical control traffic with bandwidth-hungry sensing streams over a fixed spectrum allocation. This paper proposes a Head-of-Line (HoL) Enhanced Hybrid Lyapunov scheduler for 5G-TSN networks that augments a drift-plus-penalty queue-stability core with an explicit head-of-line delay term and a class-isolation mechanism. The scheduler is evaluated in a 3GPP Indoor Factory scenario with standardized 3GPP fading, spatial consistency, and clutter blockage, using Automated Guided Vehicles (AGVs) generating concurrent URLLC, eMBB, and mMTC flows mapped to dedicated QoS-flow bearers. A fleet-size sweep of 5--30 AGVs on a fixed 20\,MHz carrier reveals a scheduler-independent capacity threshold at approximately 12 vehicles, verified by resource-block saturation. Below the threshold, the proposed scheduler is competitive with the strongest delay-aware baselines and its head-of-line term halves the URLLC deadline-miss ratio relative to the plain Lyapunov formulation. Beyond the threshold, it degrades selectively where the baselines collapse: at $2.5\times$ overload it delivers $1.8\times$ more URLLC traffic than the proportional-fair and delay-budget-aware baselines with a $\approx 4$--$7\times$ shorter 99th-percentile latency, resolving the capacity shortfall in favour of the critical classes instead of spreading it across the traffic mix, at a quantified cost in aggregate cell throughput. The results position Lyapunov-based scheduling as an attractive overload-robustness mechanism for industrial 5G deployments that must remain dependable under unexpected load conditions.