Performance of a 5G NPN in industry: statistical analysis and application to black channel protocols

Due to an increasing need for mobility on the factory floor, future industrial applications will often use wireless technologies like 5G. The necessarily high reliability not only needs to be designed into the wireless communication technology, but also has to be experimentally verified. Events that degrade the reliability of highly available systems are rare. Additionally, correlation is inherent to wireless channels and an analysis method that is able to cope with those two challenges is needed. Thus, in this work our aim is to provide such a method. We evaluate the practical usage of the limited relative error (LRE) algorithm and discuss how to obtain confidence intervals based on it. Thereby, the standard normal distribution is approximated, which leads to biased results. We illustrate this by the usage of the Berry-Esseen theorem. To overcome the bias the LRE algorithm is enhanced with moving block bootstrapping (MBB). We call this new method bootstrapping LRE algorithm. We use measurement data from a 5G network for our analysis. Further, the usability of the 5G network for communication purposes based on the black channel paradigm is evaluated with the 5G measurement data and its statistical analysis. Thereby, the performance parameters of cycle time and reliability of the black channel in 5G are determined.