Since the German Federal Network Agency started the application process for local 5G campus networks in November 2019, there has been an increasing number of reports about companies that have been allocated the corresponding local frequencies. There, different concepts can be implemented, from the completely private solution without a connection to the public Internet, through hybrid approaches, to network slices over shared frequencies of public 5G antennas. When reporting on newly commissioned 5G campus networks, reference is often made to the relatively low license costs that are incurred depending on the allocated bandwidth, the area, and the duration of the allocation. From an IP perspective, however, these statements must be critically questioned. The license fees set by the Federal Network Agency relate to the local use of certain frequencies for 5G applications.

However, these license fees do not include payments for the use of the 5G technology standard. This technology standard was developed by a large number of companies and institutions in order to ensure the interoperability of the actors in 5G systems. Technical specifications were therefore established to ensure that systems and devices from different manufacturers can also communicate with one another. Most of the technical solutions stored in the standard specifications are protected by patents. More than 20,000 patent families (almost 100,000 individual patents) have already been declared as standard essential for the implementation of the 5G standard, with the scope of the standard specifications and thus the number of relevant intellectual property rights growing continuously. Every owner of standard-essential patents basically has the right to demand license fees from the implementers of the standard – regardless of the payments already made to the Federal Network Agency. The modalities for the collection of patent licenses, i.e. who pays how much to whom for the implementation of which standard specifications, have not yet emerged. There are many indications that different models will emerge depending on the industry and application.

While standard essential patents and their respective owners cannot yet be clearly defined, a large number of use cases are implemented in the industrial use of 5G networks, which in turn are protected by patents, but which do not fall under the specifications of the standard. It is precisely these use cases, from machine-to-machine communication through augmented reality applications to simulations based on real-time data, which were previously not possible due to data rates, latency and reliability, which are now becoming the driving force behind the implementation of 5G, in particular in local applications. Digital solutions that are necessary for the implementation of such use cases are patented with increasing intensity, as companies want to secure a strong starting position for the race of 5G-based services and systems through exclusive use cases.

These framework conditions give rise to substantial risks for the industrial implementation of 5G campus networks since a single patent owner is enough to shut down an entire production facility. In view of the large number of owners of potentially relevant property rights, suitable measures should be taken to limit these risks more clearly and to formulate appropriate risk control measures. In order to make the risks (in particular with regard to patents not considered relevant to the standard) accessible and thus manageable, the first step is to create a sound information base. This means that the use cases that come into play in the specific application must be identified, concretized, and described. A corresponding patent search, preferably with suitable AI tools, can then be set up based on such a description. From the structuring and analysis of the search results (e.g. number of relevant patents, particularly dangerous intellectual property rights, number and assessment of the behavior of patent owners), specific measures can then be worked out for the main risk areas.