The ability to get information about future UE locations provides big benefits to a number of use cases. One such use case involves “connected cars”, a use case in which multiple network slices are used for multiple purposes during the whole trajectory of the vehicle. It is important to properly manage the different demands of these different slices. Currently, connected cars primarily connect for entertainment, data collection, and basic driving instructions. In the future, however, there will be Vehicle-to-Everything (V2X) demands over Ultra-Reliable Low-Latency Communication (URLLC), so it will be necessary to maintain the UE within reliable coverage as much as possible, e.g., within the Low Band. On the other hand, for entertainment network slices, the goal may be to keep the UE on cheaper cost per bandwidth slices (e.g., Millimeter Wave (mmWave)/High Band or Mid-Band) or even to off-load onto an unlicensed spectrum as much as possible. This task will be made significantly easier with the knowledge of future UE locations now made available by the systems and methods provided herein.

The concepts present herein are not limited to cars and trucks, however. The same concepts could be applied to aerial vehicles, such as UAVs, drones, or even airplanes, all of which also can have a Three-Dimensional (3D) UE mobility trajectory, e.g., one that also includes altitude. Having advance knowledge of the UE trajectory in a three dimensional geographic space allows an operator to adjust terrestrial and aerial (A2G) networks, which may involve the use of satellites, balloons, and beamforming of signals along the paths of these flying UEs.

Yet another application of knowledge of future UE locations is to provide sufficient network resources to crowded hot spots, such as airports, malls, sports arenas, and so on, to manage the high network demands.