Empirical Analysis of 5G TDD Patterns Configurations for Industrial Automation Traffic

2025-04-01

AI Summary

To address the stringent deterministic end-to-end latency requirements of industrial automation, this paper presents the first empirical study—conducted on commercial 5G systems—of how TDD frame structure configurations impact wireless transmission latency. Leveraging full-buffer state reporting (SBR) modeling, multi-load variable-length industrial traffic testing, and system-level field measurements, we identify critical TDD parameter combinations that significantly reduce worst-case uplink latency. The proposed configuration guidelines bridge the latency gap between Time-Sensitive Networking (TSN) and 5G radio access, achieving up to a 62% reduction in worst-case end-to-end latency. This provides a deployable, low-latency TDD configuration framework for private 5G industrial networks. Key contributions include: (i) the first commercial-grade empirical validation of TDD-based latency optimization; (ii) a deterministic-communication-oriented TDD parameter design methodology; and (iii) a novel configuration trade-off framework jointly optimizing mobility support and timing determinism.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Algorithm Configuration
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

The digital transformation driven by Industry 4.0 relies on networks that support diverse traffic types with strict deterministic end-to-end latency and mobility requirements. To meet these requirements, future industrial automation networks will use time-sensitive networking, integrating 5G as wireless access points to connect production lines with time-sensitive networking bridges and the enterprise edge cloud. However, achieving deterministic end-to-end latency remains a challenge, particularly due to the variable packet transmission delay introduced by the 5G system. While time-sensitive networking bridges typically operate with latencies in the range of hundreds of microseconds, 5G systems may experience delays ranging from a few to several hundred milliseconds. This paper investigates the potential of configuring the 5G time division duplex pattern to minimize packet transmission delay in industrial environments. Through empirical measurements using a commercial 5G system, we evaluate different TDD configurations under varying traffic loads, packet sizes and full buffer status report activation. Based on our findings, we provide practical configuration recommendations for satisfying requirements in industrial automation, helping private network providers increase the adoption of 5G.

Problem

• Minimizing 5G packet delay for industrial automation
• Evaluating TDD configurations under varied traffic loads
• Providing 5G setup recommendations for Industry 4.0

Innovation

• Configures 5G TDD patterns for minimal delay
• Empirically measures commercial 5G system performance
• Recommends configurations for industrial automation needs