# 5G Beyond 3 GPP Release 15 for Connected Automated Mobility in Cross-Border Contexts
## 4 Cross-Border Use Case Implementations
### Extended Sensors  
\"Extended sensors\" aims to expand data and environmental knowledge with information coming from sensors from surrounding systems such as RSUs or vehicles, as illustrated in Figure 6. The heterogeneity on the network interfaces of different systems makes multi-radio [14] support necessary. Once the discovery protocol has been performed and the handshake between the data  
Figure 5: Platooning scenario of the proposed solution.  
source and consumer is done, the sidelink communications, such as PC5 C-V2X and 5G NR sidelink [22], allow peers to communicate without management overheads from the network infrastructure. Here, specifically the edge computing architecture [11] makes the difference, as the overheads for onboard computing resources can be offloaded to edge processing resources compiling, filtering and processing the raw data from vehicles to provide onboard systems with trusted and relevant metadata to be used by the onboard driving systems.  
From the latency perspective, sidelink communications [22] make participant communications more direct and quicker. Furthermore, zero latency of edge computing enabled services [11] will bring environmental understanding closer to the users empowering systems shipped at the vehicles with more additional sensor sources. Specifically, edge services linked to discovery and security can boost quality negotiation, selection of region of interest and credentials exchange with an edge entity with a higher standing point to manage configurations according to coordination policies and local performance context, including radio link congestion or vehicles' computation capacity. In a cross-border context, the utilisation of different edge providers would need common and standard protocol stacks and formats to ensure that common APIs and seamless service provisioning could be done, decoupling services from sensors and infrastructure vendors.  
Again, features such as positioning of 5G NR [19], based on the use of a location server similar to LTE, may help to improve accuracy from sensors. This architecture-wise technique employs a positioning reference signal (PRS) for the downlink-positioning, correlating the time of arrival (ToA) and sounding reference signals (SRSs) for the uplink-positioning, estimating the received power, the angle of arrival and the round-trip time (RTT). Moreover, broadcast and multicast communications [40] could ease the discovery protocol of the available sensors, especially as singular video streams from sensors ahead are repeatedly subscribed by vehicles at the back. In any case, here, the speed and reliability of network handover and roaming are not so critical, as the onboard driving systems must be autonomous and the goal is to find and consume potentially relevant data streams from outside the vehicle.  
For the QoS slicing feature it is important here to include processing features of the video stream destination to match the data source, not only with the network performance as described in [40], but also with the computation capacity of the vehicle consuming a data flow.  
Figure 6: Extended sensors scenario of the proposed solution.