On Weighted K-Means User Clustering for Flying Ad Hoc Networks in Disaster Scenarios

Flying ad hoc networks (FANETs) based on unmanned aerial vehicles (UAVs) can efficiently accomplish connectivity in post-disaster recovery scenarios. In this paper, a non-orthogonal multiple access based FANET is considered comprising of cooperative UAVs. The UAVs act as decode-and-forward relays serving a cluster of user equipments (UEs) in their coverage area. The partitioning of UEs around their nearest UAV is performed using a weighted K-means clustering approach. In particular, the induced weighting accounts for the feature that UAVs in different regions of a disaster scenario may operate with different transmit powers. The outage probability of the considered FANET in the presence of Nakagami-m fading is assessed.