Placement of UAV-Mounted Mobile Base Station through User Load-Feature K-means Clustering
This addresses the challenge of optimizing UAV placement for cellular network coverage during peak traffic events, but it is incremental as it builds on existing clustering methods with a new feature.
The paper tackles the problem of placing UAV-mounted mobile base stations to handle temporary high traffic in cellular networks by proposing a new feature for K-means clustering that incorporates user required traffic, resulting in UAVs being placed closer to high-traffic users to achieve higher performance.
Temporary high traffic requests in cellular networks is a challenging problem to address. Recent advances in Unmanned Aerial Vehicles applied to cover these types of traffics. UAV -Mounted Mobile Base Stations placement is a challenging problem to achieve high performance. Different approaches have been proposed; however, user required traffic is not considered in UAV placement. We propose a new feature to apply to K-means clustering to find the optimum clusters. User required traffic is defined as a new feature to assign users to the UAVs. Our simulation results show that UAVs could be placed closer to the high traffic users to achieve higher performance.