## 2 Related Work
### Performance Measurement of Cellular Networks  
The performance requirements of cellular networks with respect to logistic applications in the context of Industry 4.0 was subject to recent research [7]. The authors consider 5G to be the connectivity solution addressing all logistics needs from manufacturing floors and warehouses to worldwide material transportation. The temporal behavior of the LTE standard parameters RSRP and RSRQ has been subject to research by [PERSON] et al. [25; 33] in 2020. RSRP in three specific, static locations was found to be almost constant over periods up to several days. Thus, in this study, RSRP is measured and analyzed to figure out, if it is a valid indicator also for the spatial characterization of LTE networks. The measurement of the QoS of LTE networks is addressed by several standards [21; 24], that define the End-to-End QoS and include the assessment based on the perspectives of the final user and the service provider. The more recent norm ETSI TS 102 250-2 [21] includes the QoS for the applications E-mail, File Transfer, Multimedia Messaging Services (MMS), Mobile Broadcast, Ping, Push-to-talk over Cellular (PoC), Short Message Service (SMS), Streaming,Telephony, Video Telephony, and Web Browsing. Obviously, upcoming applications with relevance to smart logistics have not been included. The experimental analysis of cellular networks has been subject to continuous research. [PERSON] et al. [31] emphasize the need to monitor objective parameters to automatically measure and improve the end user's Quality of Experience (QoE). [PERSON] et al. [32] identify the limitations of LTE for automotive off-board applications with respect to transmission delays and packet discard rates. In [26], the authors measure and compare the spatio-temporal performance of cellular and 802.11 WiFi communication based on speed-tests on end-user devices. They find a strong variation over the time of day and a significant spatial consistency. Using end-user devices and crowd-sourced datasets has also been the base for a study by [PERSON] et al. [22]. The authors confirmed that the QoS and coverage of cellular networks can be explained by measuring RSRP, which is one of the three parameters analyzed within this study. In a text by [PERSON] et al. [23], different crowd-sourced parameters are analyzed to identify an operator. The latency was found to be the most important feature. However, in contrast to this study, the dataset did not contain any position information. In a more recent study by [PERSON] et al. [34], lower-layer indicators, like RSRP, RSRQ, and RSSI, are used to generate higher layer metrics and assess overall End-to-End (E2E) performance. The article confirms the relevance of the parameters under investigation in this study. According to [35], Radio Access Network (RAN) problems are causing 48% of all network performance issues. The authors create a technology-agnostic methodology to assess the QoE based on Key Quality Indicators (KQIs). In [28], the authors perform drive tests in rural Malaysia based on mobile phones to measure the performance of the 3G and 4G networks for web browsing and video streaming applications. In comparison, based on an overall statistical evaluation, they find the 4G network to perform better than the 3G cellular network. In a similar study for urban areas of Malaysia [29], a better performance than in rural areas was observed. However, the evaluation was limited to an overall statistical assessment, and neither time- nor position-related dependencies were considered. In a very recent study by [PERSON] et al. [30], 3G and 4G networks were assessed for different cities in Oman in mobile phone-based, one-time drive tests. The authors observed local RSRP levels below \(-100\) dBmW, which potentially lead to the described packet losses. An overview of the related publications is given in Table 2.  
The status of the extension and quality of the cellular network is regularly self-assessed by the providers in Germany [5; 6; 36].