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Empirical Evaluation of Wireless Technologies for Resilient and Reliable Remote Control: 5G, Starlink, and Multi-Connectivity
Author(s) -
Weifan Zhang,
Rasmus Suhr Mogensen,
Carmen Covadonga Blanco Gonzalez,
Sebastian Bro Damsgaard,
Sokol Kosta,
Preben E. Mogensen
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3620752
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Wireless technologies are increasingly adopted for industrial video monitoring and remote control due to their flexibility, scalability, and broad coverage. These applications impose stringent performance requirements—packet loss below 0.05% and uplink/downlink latency under 100 ms at the 99.9th percentile. This paper presents an empirical evaluation of 5G from two Mobile Network Operators (MNOs), the Starlink satellite network, and multi-connectivity (MC) strategies across stationary and mobile (urban and rural) scenarios. We develop the Industrial Communication Measurement Tools (ICMT), a UDP-based tool tailored to control-centric use cases, and use it to conduct detailed measurements of Key Performance Indicators (KPIs): uplink and downlink latency, packet loss, data rate, overhead, network usage ratio, and signal quality. Our results show that 5G delivers reliable performance under stationary conditions but degrades under mobility. Starlink shows significantly higher packet loss rates than 5G in our measurements. Moreover, rural performance is consistently inferior to urban. For 5G, signal quality shows a correlation with network performance, especially in the uplink. We also evaluate two MC strategies—selection and switching—demonstrating that selection significantly reduces latency and packet loss but introduces high overhead, while switching offers a more balanced trade-off between performance and overhead. Only 5G from MNO1 and specific MC configurations satisfy the requirements of video monitoring and remote control in stationary or urban mobile scenarios, while none meet them in the rural area. These findings provide valuable guidance for choosing suitable wireless technologies for industrial video monitoring and remote control.

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