Wireless- and 5G-enabled industrial automation is expected to include a plethora of different applications with a wide variety of requirements. In this article, evaluations are undertaken for the deployment of 5G in realistic industrial production environments with realistic deployment settings. Both deployments using commercial 5G systems and a 5G prototype system including pre-commercial and standard compliant URLLC functionality have been investigated. Systematic latency and reliability measurements were performed, over the air and in live networks, for different packet sizes, different devices, and networks with different capabilities (at different sites) to characterize the expected performance. The results indicate that today’s 5G latency performance significantly depends on packet size, transmission direction (uplink or downlink), and network configuration as well as on the end device’s design and capabilities. Our over-the-air measurements also empirically show that 5G technology and future networks have the capability of providing one-way latency of around 1 ms in both uplink and downlink for the various packet sizes tested. It is concluded that the requirements for very low latencies can be achieved with high reliability guarantees, as required in some of the most stringent industrial IoT applications.

Cyber–physical systems are created at the intersection of physical processes, networking, and computation. For applications developed to implement cyber–physical interactions, in the face of limited resources, an optimization of efficiency needs to be handled across all entities—communication, computing, and control. This gives rise to the emerging area of “co-design” that addresses the challenge of designing applications or systems at the intersection of control, communication, and compute when these domains can and should no longer be considered to be fully independent. In this article a co-design framework is presented that provides a structured way of addressing the co-design problem. Different co-design degrees are specified that group application design approaches according to their needs on criticality/dependability and relate these to the knowledge, insights, and required interactions with the communication and computation infrastructure. The applicability of the framework is illustrated for the example of autonomous mobile robots, showing how different co-design degrees exploit the relationships and permit the identification of technical solutions that achieve improved resource efficiency, increased robustness, and improved performance compared to traditional application design approaches. The framework is of relevance both for concrete near-term application implementation design as well as more futuristic concept development.

The 5G non-public network deployments for industrial applications are becoming highly interesting for industries and enterprises owing to dependable wireless performance characteristics. With an increasing trend of network deployments in local licensed and/or shared spectrum, coexistence issues naturally arise. In this article, we present our detailed empirical results on the performance impact of a 5G NR indoor non-public network from a 5G NR outdoor network operating in the same mid-band spectrum. We present experimental results on the uplink and downlink performance impact of a non-public indoor network deployed on an industrial shopfloor. Our results quantify the impact on the uplink and downlink performance characteristics based on realistic traffic loads in a non-public indoor network when using synchronized and unsynchronized Time Division Duplex (TDD) patterns, different UE deployment locations and interference levels. We also present results on mitigating interference effects through robust link adaptation techniques. We believe that this is the first article, which reports quantified 5G NR cochannel coexistence results based on a detailed and systematic study, and provides signficant insights on the cochannel coexistence behavior in realistic deployment scenarios of an industrial shopfloor.