UAV-Enabled Disaster Recovery and Management

Abstract

Due to the unavailability of the traditional network in disaster scenarios, users are unable to communicate with each other or the rescue team. In this regard, Unmanned Aerial Vehicle (UAV) as an Aerial Base Station (ABS) and Device-to-Device communication (D2D) provide an alternative for enabling end-to-end connectivity among users. In this paper, we proposed a k-value selection method relating three communication factors: area, receiver sensitivity, and density. Two UAV trajectory planning algorithms are pro posed based on the RSAND scheme and K-means centroids. In addition, two clustering schemes are proposed based on UAV trajectory to select a more suitable node as a cluster head (CH) to manage intra-cluster distances. The performance of proposed schemes is analyzed based on average end-to-end outage probability. Simulation results show the validity of proposed algorithms which have better performance over benchmark schemes in terms of average end-to-end outage probability and trajectory length. Moreover, a case study of a real terrorist attack scenario is carried out to validate the efficacy of the proposed solution.