The "future of everything connected" needs a novel 3D network architecture approach to provide connectivity anywhere and anytime.
To this end, 6G-TakeOff will strive for a uniform 3D communications network, in which flying network nodes provide functionalities together with terrestrial network components dynamically and according to demand. The holistic approach required for this opens up space for innovations that go beyond the possibilities of the 3GPP 5G-NTN approach by exploiting the full potential of flying network components.
Classes of network nodes include IoT/end-user devices, terrestrial access nodes, and 3D components such as Low Altitude Platforms (LAPS), High Altitude Platforms (HAPS), and satellites with their specific characteristics. A 6G system will connect these network components in a highly flexible, autonomous, where necessary infrastructure-independent way.
- Organic network behavior, meaning network nodes can dynamically join or leave the network,
- security mechanisms for authenticating newly joining network nodes, which will operate without a permanent connection to a control center on the ground,
- dynamic relocation of network functionalities (radio access and core network) and associated relocation of information flows according to current Quality of Service (QoS) requirements,
- a connectivity management system that automatically and autonomously monitors the availability of connections between neighboring network nodes and selects the best possible routes for the traffic flows to be transported in terms of resource consumption, energy consumption and cost efficiency,
- a “unified access” mechanism that automatically selects the network access that best meets the customer’s communication needs from all available network accesses,
- reconfigurable hardware and microelectronics for communication payloads of flying nodes to implement dynamic shifting of network functionalities,
- antenna systems with high gains both in the ground terminals and in the flying network nodes to bridge the signal losses due to long distances between the network nodes.
