Geolocation Clustering for Radio Resource Management in 6G Networks

The rise of IoT signals towards the increased integration of AI into day-to-day life, with nearly all the elements in the surroundings being embedded with sensors. This leads to data-intensive applications requiring versatile wireless connectivity to deliver results in real-time. In order to achieve these ambitious targets, 6G is being touted to bring about massive software as well as hardware innovations; ranging from AI-enabled network architecture to mobile edge computing.A major hardware innovation in 6G, as compared to 5G, is the introduction of mobile base-stations which would provide dynamic network reconfiguration and increased connectivity. We propose a clustering methodology in this paper to enable optimum resource allocation by assigning the base stations to hot-spots with heavy traffic requirements. This would provide a way for all user devices to be covered under the network without putting excessive strain on the network resources.