# An Experimental Framework for 5G Wireless System Integration into Industry 4.0 Applications
## 3 Experimental Framework for 5G Integration
### 5G Hardware and Software Prototyping Tools
This mode simplifies the integration setup and the use of the WMAGW as the SW is more computationally efficient than for the L2-tunnel mode, since we are simply bridging the ethernet and wireless interface of the gateways and establishing routing paths, but its application is not always possible especially when addressing legacy production control systems. WMAGWs are used from STEP 4 and above of the operational framework flow. When utilizing the WMAGW in device-to-device communication mode, two boxes are needed; one at each of the machinery devices that are to be connected over 5G. In the case of addressing a centralized infrastructure-mode case, e.g., enabling the 5G communication between a production station and a factory controller located in a server room, only one physical WMAGW device is needed and deployed at the machinery side, while at the other end only the SW is deployed to encapsulate/decapsulate the data. The implemented functional architecture of the different boxes is the same in all different evolution versions (v). However, the specific choice of HW components has evolved throughout our industrial research and experimentation activities and might be different from version to version, leading to different form factors, as illustrated in Figure 4b,c for two  
Figure 4: **(a)** Functional block diagram of the WMAGWs (operating in device-to-device L2-tunnel mode). Note: for IP-based operation, the alternative path is chosen via SW configuration. Infrastructure mode is supported by using the exam same functional blocks. **(b)** Picture of the implemented WMAGW prototype (v2) including details on the different HW components. **(c)** Picture of the implemented WMAGW prototype (v3) including details on the different HW components. different versions of the WMAGW (v2 and v3). As a reference for the different designs, Table 1 summarizes the main hardware and software components implemented in the latest versions of the different devices. In the specific case of the WMAGW, the modem and antenna configuration might be different depending on the HW version and the intended use of the device. The WMAGW (v3) allows for the installation of up to four modems, and in its reference design (displayed in Figure 4c) builds up two 5G modems and two Wi-Fi six modems. With this configuration, the WMAGW allows for operation over either of the technologies individually, using one or two paths, or over both technologies enabling multi-access multi-connectivity (for increased reliability) [26]. The flexibility in the choice of operational modems and technologies is a key advantage compared to the industrial devices in the market such as the ones from HMS [20], SIEMENS [21] or Robustel [22] which typically implement and support only closed configurations. Further, the state-of-the-art 5G equipment for industrial use is still undergoing its initial commercialization phase and it is not mature enough yet and might not operate fully as expected. Currently, commercial devices might experience some of the same challenges that we typically encounter in our integration research. Initial interfacing with recently deployed and configured 5G networks typically results in connectivity issues or performance instability that requires dedicated debugging and firmware updates and tuning. Thus, being in control of the full device implementation, as it is the case with the WMAGW, is of great advantage. Being in control of the SW implementation also plays in our favor when, for example, 5G connectivity is stable but debugging is needed for the advanced L2 tunneling or multi-connectivity schemes. 3 packet inter-arrival times (PIAT) (1, 10 and 100) ms. Calibration test results were collected over a long-enough time of operation to guarantee that we had enough statistics to claim a reliable accuracy up to the 99.9% level, i.e., 10\({}^{-3}\) level in the below complementary cumulative distribution functions (CCDF) [35].