Cracking the Microsecond: An Efficient and Precise Time Synchronization Scheme for Hybrid 5G-TSN Networks

2025-11-18

AI Summary

To address the challenge of achieving microsecond-level time synchronization in industrial IoT (IIoT) environments—where hardware limitations hinder seamless integration of 5G and Time-Sensitive Networking (TSN)—this paper proposes a lightweight, hardware-agnostic synchronization scheme. The method innovatively reconfigures generic user equipment (UE) as a combined grandmaster and boundary clock node, enabling unified time distribution across the 5G core network, radio access network (RAN), and factory wired TSN infrastructure. Leveraging OpenAirInterface and software-defined radio (SDR), we implement a testbed that employs a moving-average filter to dynamically estimate and compensate for both clock offset and frequency drift. Experimental results demonstrate stable synchronization accuracy of ±50 ns in hybrid 5G-TSN networks, satisfying sub-microsecond industrial requirements. The solution offers significant practical advantages: low cost, minimal hardware dependency, and straightforward deployment—making it suitable for real-world IIoT applications.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Hardware-aware ML
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Achieving precise time synchronization in wireless systems is essential for both industrial applications and 5G, where sub-microsecond accuracy is required. However, since the Industrial Internet of Things (IIoT) market is negligible compared to the consumer electronics market, the so-called IIoT enhancements have not yet been implemented in silicon. Moreover, there is no guarantee that this situation will change soon. Thus, alternative solutions must be explored. This paper addresses this challenge by introducing a scheme that uses a protocol capable of leveraging existing infrastructure to synchronize User Equipments (UEs), with one of the UEs serving as the master. If this master is connected via a wired link to the factory network, it can also function as a boundary clock for the factory network, including any Time-Sensitive Networking (TSN) network. Furthermore, the 5G Core Network (5GC) and 5G Base Station (gNB) can also be synchronized if they are connected either to the factory network or to the master UE. The proposed solution is implemented and evaluated on a hardware testbed using OpenAirInterface (OAI) and Software Defined Radios (SDRs). Time offset and clock skew are analyzed using a moving average filter with various window sizes. Results show that a filter size of 1024 provides the best accuracy for offset prediction between UEs. In a controlled lab environment, the approach consistently achieves synchronization within +/-50 ns, leaving sufficient margin for synchronization errors in real deployments while still maintaining sub-microsecond accuracy. These findings demonstrate the feasibility and high performance of the proposed protocol for stringent industrial use cases.

Problem

• Achieving sub-microsecond time synchronization in hybrid 5G-TSN networks
• Leveraging existing infrastructure for synchronization without hardware enhancements
• Synchronizing User Equipments and factory networks using a master UE

Innovation

• Leverages existing infrastructure for UE synchronization
• Uses master UE as boundary clock for TSN
• Implements moving average filter for precision