The nascTime framework on OMNeT++/Simu5G is used to evaluate how many TSN endpoints a single 5G NR cell can bridge before per-flow QoS degrades, showing that sub-3 ms TSN deadlines may require radio-configuration changes such as configured grants or higher numerology.
Abstract
3GPP Release 16 enables a 5G system to operate as a transparent IEEE 802.1 TSN bridge, but its scalability under heterogeneous industrial workloads remains insufficiently characterised. This paper uses the nascTime framework on OMNeT++/Simu5G to evaluate how many TSN endpoints a single 5G NR cell can bridge before per-flow QoS degrades. We model closed-loop control, machine vision, bulk telemetry, and IEEE 802.1AS traffic over a four-bearer SDAP architec- ture, varying the number of endpoints from 1 to 40, MAC scheduler, radio bandwidth (10 MHz and 20 MHz), and channel model. Results show three operating regimes. Below saturation, non-DRR schedulers perform similarly; near saturation, QoS- aware PF reduces critical-flow P99 latency by up to two or- ders of magnitude relative to channel-aware and fairness-based schedulers; and under overload, only QoS-PF maintains near- complete delivery for the highest-priority traffic. Across the two evaluated bandwidths, the saturation threshold approximately doubles when bandwidth doubles. We also show that isolating IEEE 802.1AS/gPTP traffic on a dedicated high-priority radio bearer reduces clock-servo instability, although endpoints carry- ing lower-priority data still experience elevated synchronisation delay under saturation because of reduced MAC scheduling frequency. Finally, the evaluated sub-6 GHz, 30 kHz-SCS con- figuration exhibits an effective latency floor of approximately 2.25 ms, indicating that sub-3 ms TSN deadlines may require radio-configuration changes such as configured grants or higher numerology
Current end-to-end congestion-control feedback is too slow to track rapid wireless dynamics in cellular networks. We identify Grant-to-Buffer Ratio (GBR)—the ratio of base-station uplink grants to mobile-reported demand—as a millisecond-scale RAN signal of uplink resource scarcity. Measurements across AT&T, Verizon, and T-Mobile LTE/5G FDD/TDD deployments show that GBR tracks base-station uplink load and reveals congestion earlier than end-to-end feedback. Because GBR is derived from the mandatory BSR-grant exchange, it requires no base-station changes and captures scheduler decisions at their native timescale. We then design GBR-CC, a dual-loop controller that updates the sender rate on each GBR sample, using GBR for fast adaptation and end-to-end delay trends as a conservative fallback. This design lets the sender react before queues inflate while still handling non-radio bottlenecks through the outer loop. GBR-CC runs on commodity mobile devices without extra hardware or external tools. Experiments on commercial cellular networks show that GBR-CC improves average throughput over GCC by 50%, while reducing median playout latency by 32–53% and freeze rate by 60%; compared with BBR, it improves average throughput by 5% and halves median RTT.
Qiang Wu, Yuxin Liu, Tianyang Zhang et al.· Conference on Applications,...· 0 citations
B-CUBE is proposed, a novel burst-aware 5G-TSN architecture that equips each industrial node with co-deployed TSN and 5G system bridges to enable wired, wireless, and dual-mode transmission, and designs a set of e-cient cross-domain mixed-flow scheduling algorithms.
Yi Xue, Jie Jia, Hao-Yang Mao et al.· Science China Information Sc...· 0 citations
The rapid evolution of 5G and emerging 6G networks requires optical access systems to support immersive extended reality (XR) services with stringent quality-of-service (QoS) requirements, like ultra-low latency and high bandwidth. However, conventional dynamic bandwidth allocation (DBA) schemes in passive optical networks (PONs) allocate upstream bandwidth solely based on reported queue occupancy, without considering the unique characteristics of XR traffic. To address these limitations, we propose an XR-aware Predictive (XP)-DBA scheme that integrates XR traffic prediction, deadline-aware scheduling, adaptive grant control, and a cycle-controller to proactively allocate bandwidth, prioritize latency-critical packets, and limit polling-cycle growth. We also derive closed-form analytical expressions to characterize XR-specific stability and delay feasibility in PON systems. We evaluate XP-DBA under standardized and burst-enhanced XR traffic models across varying XR user densities and transmission distances of up to 100 km. The results show that XP-DBA will reduce latency, jitter, and polling-cycle time while increasing throughput and supporting higher XR user densities under heavy network loads without violating XR delay bounds. These findings establish XP-DBA as an efficient and scalable scheduling solution for next-generation immersive XR services over long-reach optical access networks.
Akhilesh Patel, Y. Singh· IEEE Transactions on Network...· 0 citations
Evaluation on representative workloads demonstrates that P2CS achieves performance comparable to in-network mechanisms while significantly reducing complexity and cost, and requires minimal software changes making it readily deployable in today's datacenter infrastructure.
Ali Munir, Xiaolin Pang, Junyi Zhang· Conference on Applications,...· 0 citations
This work introduces CSIG, a protocol that delivers precise, multi-bit bottleneck congestion signals via a fixed-length Ethernet header, and proposes Fast Ramp-Up, a congestion control primitive that leverages these bottleneck signals to reduce median RPC latency by 20% and unclaimed bandwidth by 60% in production.
Abhiram Ravi, Nandita Dukkipati, Weiwu Pang et al.· Conference on Applications,...· 0 citations
Cellular networks are integrating Artificial Intelli- gence (AI) into radio access network control. The MAC scheduler is a promising target because it allocates a limited resource, spectrum, at every slot, under competing latency, throughput, and reliability requirements. However, most learning-based sched- ulers are evaluated only in simulation. Production schedulers are difficult to modify, and realistic stress tests require more radio hardware than most laboratories can provide. We present MAC-Gyver, an open-source framework for developing and evaluating scheduling applications that execute directly inside the OpenAirInterface scheduler. It exposes scheduler observations and controls through typed interfaces while preserving the underlying protocol and real-time execution paths. The same applications run over the air and in mac-emu, a PHY-less emulator that executes the unmodified OpenAirInterface Layer 2 stack for up to 90 users on one host at real-time slot pace, with a 3GPP-compliant channel model. To showcase the flexibility of MAC-Gyver, we evaluate two use cases. A proactive uplink scheduler predicts packet arrivals and roughly halves median round-trip latency. A frequency-selective uplink scheduler selects contiguous sub-bands from per-PRB sounding observations and is evaluated across mobility and power-limited operating points against an offline scheduling ceiling. Together, they show how the same production stack can be an AI playground that supports implementation, controlled evaluation, and over-the-air validation through complementary scheduling use cases.
M. Elkael, Reshma Prasad, Tamerlan Aghayev et al.· arXiv.org· 0 citations
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