Comparative Performance Evaluation of 5G-TSN Applications in Indoor Factory Environments

TL;DR

The paper addresses the challenge of enabling deterministic QoS in industrial networks by evaluating 5G-TSN performance for indoor factory applications through simulations. It implements an Indoor Factory Profile based on 3GPP TR 38.901 within a 5G-TSN network model and analyzes mobility-driven use cases, including AGV-like traffic with distinct priority classes. Key contributions include SINR assessment across multiple indoor factory profiles, end-to-end latency analysis for latency-sensitive and non-critical traffic, and HARQ reliability trends as distance and mobility vary. The findings suggest that 5G-TSN can support latency-critical operations in controlled indoor factory environments, providing a baseline for future real-world validation and integration with industrial automation systems.

Abstract

While Time-Sensitive Networking (TSN) enhances the determinism, real-time capabilities, and reliability of Ethernet, future industrial networks will not only use wired but increasingly wireless communications. Wireless networks enable mobility, have lower costs, and are easier to deploy. However, for many industrial applications, wired connections remain the preferred choice, particularly those requiring strict latency bounds and ultra-reliable data flows, such as for controlling machinery or managing power electronics. The emergence of 5G, with its Ultra-Reliable Low-Latency Communication (URLLC) promises to enable high data rates, ultra-low latency, and minimal jitter, presenting a new opportunity for wireless industrial networks. However, as 5G networks include wired links from the base station towards the core network, a combination of 5G with time-sensitive networking is needed to guarantee stringent QoS requirements. In this paper, we evaluate 5G-TSN performance for different indoor factory applications and environments through simulations. Our findings demonstrate that 5G-TSN can address latency-sensitive scenarios in indoor factory environments.

Figures (6)

• Figure 1: 5G-TSN Indoor Factory Environment
• Figure 2: 5G-Based MiR architecture in 5G-TSN network
• Figure 3: SINR evaluation with different InF profile
• Figure 4: End-to-End delay with varying data rate
• Figure 5: HARQ error rate with different profiles and distances