An Efficient Hypergraph Based Clustering Technique for UAV-Enabled D2D Cellular Networks

Device-to-Device (D2D) communication and Un-manned Aerial Vehicle (UAV) femtocells play crucial roles in addressing the growing data demands of Fifth-Generation (5G) cellular networks. The conventional technique, where the UAV serves each User Equipment (UE) individually, increases energy consumption and reduces energy efficiency. Therefore, it is imperative to develop efficient clustering techniques that simultaneously improve system performance and energy efficiency. This paper introduces a novel clustering technique aimed at minimizing energy consumption in UAV-enabled D2D cellular networks. The proposed technique leverages hypergraph theory for cluster formation and employs the Particle Swarm Optimization (PSO) algorithm to select a central user within each cluster. The selection of an optimal central user takes into account various factors, including distance, residual energy, and degree centrality of the UEs. Through simulations, the proposed technique demonstrates superior performance in terms of system throughput, energy consumption, and energy efficiency when compared to traditional techniques.