Placement of UAV-Mounted Mobile Base Station through User Load-Feature K-means Clustering

TL;DR

This paper introduces a novel K-means clustering approach incorporating user traffic demand as a feature to optimize UAV-mounted base station placement for improved cellular network performance during high traffic periods.

Contribution

It proposes a new feature for K-means clustering that considers user traffic demand, enhancing UAV placement strategies for better network coverage.

Findings

UAVs placed closer to high traffic users improve network performance

Incorporating traffic demand as a feature enhances clustering effectiveness

Simulation results validate the proposed placement strategy

Abstract

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.