Dynamic Frequency Planning for Autonomous Mobile 6G in-X Subnetworks

摘要

Within the development of 6G, so-called subnetworks were proposed to serve special use cases like intra-vehicle sensor-actuator communication, robot control in industrial environments, or health monitoring. These use cases are characterized by extreme communication demands between the devices served by a single subnetwork. Moreover, the subnetworks will be densely deployed, with mobile and autonomous vehicles carrying the subnetwork Access Points (APs). These properties necessitate novel approaches for frequency planning in order to enable reliable communication within all subnetworks and efficient resource usage. In this context, the problem of dynamic frequency planning for mobile 6G in-X subnetworks is investigated in this paper. To this end, a multi-objective optimization problem with the objectives of minimizing frequency subband usage and subnetwork reconfigurations leveraging knowledge about future interference scenarios is formulated. Afterward, the problem is shown to be NP-hard, and two heuristic algorithms are developed. Using realistic vehicular movement data from simulations, results show that the heuristics outperform a State-of-the-Art (SotA) benchmark. Moreover, the value of knowledge about future interference scenarios is shown. Reconfigurations can be reduced by 18.91% when prioritizing subband usage and even by 33.02% when prioritizing reconfigurations if interference scenarios are known for three time steps instead of one.