by Haibin Zhang (TNO)

The Horizon 2020 EU-Taiwan collaboration Clear5G project focuses on 5G wireless solutions to empower the factories of the future. Some intermediate results of the project are also presented.

Wired networks are still dominating the industrial automation market today. However, wireless communication has advantages in some factory environments [1] [L1], for example, where chemical or metal particles are harmful to wire connectors, costing hundreds of thousands of Euros per year to maintain in a medium-to-large-sized factory. In addition, wireless communication is the most convenient (or even only) means to transmit information to or receive information from mobile robots or moving objects such as AGVs or forklift trucks. 

The Horizon 2020 EU-Taiwan collaboration project Clear5G [L2] addresses how 5G wireless networks may empower the Factories of the Future (FoF). “Clear5G” stands for “Converged wireless access for reliable 5G Machine-Type Communications for factories of the future”. The project was launched in September 2017 and will run until February 2020. Clear5G’s objective is to design, develop, validate, and demonstrate an integrated convergent wireless network for Machine Type and Mission Critical Communication (MTC/MCC) services for FoF. Clear5G aims to deliver technical solutions in the radio network domain, which can support massive deployment of connected devices, security, ultra-low latency and ultra-high reliability in FoF applications.

Various use cases in FoF pose different technical requirements on 5G, which cannot be met by any single available wireless technology. Technological versatility improves service provisioning capabilities, but meanwhile increases challenges on how to effectively manage convergence among co-existing technologies (short- and long-range, private and public, infrastructure- and ad-hoc based, etc.) at a large scale. The challenges are further increased by peak interference due to the operation of heavy machinery (e.g., switches) in typical FoF environments. With this in mind, Clear5G focuses on providing physical (PHY) layer, medium access (MAC) layer, and architectural and management enhancements to meet the strict requirements of FoF applications, thus contributing to the ITU-R objectives for the next generation mobile networks.

At the PHY layer, Clear5G studies solutions for reliable MTC that can support massive numbers of devices, achieving extreme low latency and reduced signalling and control overhead. Key technical components include adaptive frame structure and waveform, non-coherent modulation, non-orthogonal multiple access (NOMA), and physical-layer security. At the MAC layer, Clear5G focuses on solutions for integrated convergent access supporting low latency, high reliability, massive connection density, and high energy and spectrum efficiency. Both contention-based and contention-free mechanisms are considered, in potentially heterogeneous networking scenarios.  Clear5G also addresses joint PHY and MAC optimisation, in particular in the context of NOMA (for high connection density). At the architectural and management level, Clear5G designs radio network architecture and management mechanisms (with potential coexistence of public and private infrastructures) to fulfil the needs of FoF applications in terms of latency, heterogeneity, reliability, scalability and manageability. Further, energy efficiency (especially at the device side) will be among the major performance targets in the design of network architecture and management strategies. Key technical components include inter-slice management, multiple connectivity, UE relaying, SDN and data analytics tooling for network management.

Figure 1 illustrates a multi-tier 5G factory network, proposed by Clear5G [2],  providing wireless connectivity among different types of input/output (I/O) devices: URLLC and non-URLLC ones, mobile and static ones. Different network slices may be configured to support URLLC and non-URLLC services, respectively. For a slice of URLLC services, a controller may be deployed locally as close as possible to the application area (edge computing). On the other hand, for a slice of non-URLCC services a controller may be deployed in a private or public cloud for central management.  When blocking occurs, due to the presence of heavy metals and/or electro-magnetic interferences, (dynamic) UE relaying could be used to provide better coverage and higher reliability. Faster data exchange between URLLC devices could also be facilitated through device to device (D2D) communication where possible.

Figure 1: Multi-tier 5G factory network enhanced by UE relaying and D2D communication [2].
Figure 1: Multi-tier 5G factory network enhanced by UE relaying and D2D communication [2].

In the context of low latency, Clear5G addresses latency in both user plane (i.e. data transmission in RRC connected mode) and control plane (i.e. the transition from the idle/inactive mode to the connected mode). Data transmission via the control plane is enabled and (for URLLC services) as early as possible. Figure 2 exemplifies the performance of URLLC services using a proposed two-step random access procedure with data repetitions (noted as ‘5G repeat’)  in the form of the 50th, 99.9th and 99.99th percentile latency, in comparison with the state-of-the-arts (SoTA) solutions: LTE Cat-M1, Early Data Transmission – EDT (available since 3GPP Release 15). The achievable minimum latency of the ‘5G repeat’ solution is 5 ms, in comparison with 37 ms of LEE Cat-M1 and 14 ms of EDT.  Note that 3GPP has requirement of < 10 ms for control plane latency. Further note that these example results and comparison are based on a Transmission Time Interval (TTI) of 1 ms. For 5G NR, with a lower TTI length (e.g. 0.25 ms),  the minimum control plane latency could be further lowered (e.g. to 1.25 ms). 

Figure 2 Random access latency of URLLC services using the two-step procedure in comparison with SoTA solutions [3].
Figure 2: Random access latency of URLLC services using the two-step procedure in comparison with SoTA solutions [3].

Interested readers may refer to the deliverables of Clear5G for more (intermediate and detailed) results of the project.

The Clear5G consortium consists of seven European partners and four Taiwanese partners, with a combination of major corporations (FFG-Fair Friend Group, Toshiba, Turk Telekom, ADLINK), SMEs (WINGS), as well as research and academic institutions (University of Surrey-coordinator, TNO, CEA, ARGELA, III, National Taiwan University). ERCIM member TNO is technical manager of the project, with the responsibility to ensure that the scientific content of the project is of a high-standard, adhering to the objective of overcoming the technical challenges envisioned, while staying up to date with the scientific progress in areas relevant to the project.

The overall project results will be demonstrated using the facilities provided by both Taiwanese and European parties. The Taiwanese and European facilities will be coordinated to serve the same project goal. For example, the 5GIC testbed at University of Surrey will be mainly used for proof of concept demonstration and to further validate the project results in a scenario that shows and allows investigation of the coexistence of physically private and public infrastructure. A mini-PC based relaying testbed at TNO will be used to showcase the potential of UE relaying to improve coverage and communication reliability in factory scenarios where radio propagation is subject to large shadowing or blockage effects from metal objects. The final project demonstration is planned in the factory floor of ANEST IWATA Taiwan Corporation, a joint venture of FFG, for validation of project results in a near-to-real factory environment.

Link: 5GPPP White Paper "5G and the Factories of the Future"

[1] 3GPP Technical Report TR 22.804 V16.2.0: “Study on Communication for Automation in Vertical domains”, August 2018, pp. 54-103
[2] Clear5G Deliverable D4.1, “Radio Network Architecture and Management for FoF (Preliminary)”, August 2018, p. 22..
[3] Clear5G Deliverable D3.1, “Random Access Enhancement”,  August 2018, p. 45.

Please contact:
Haibin Zhang
TNO, The Netherlands
This email address is being protected from spambots. You need JavaScript enabled to view it.

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