Joint Clustering and 3-D UAV Deployment for Delay-Aware UAV-Enabled MTC Data Collection Networks

The design of timely data collection for a machine-type communication (MTC) network by unmanned-aerial-vehicle (UAV) platform is investigated. The ground-based MTC devices are clustered for efficient service, and the UAV station's deployment in the 3-D space is optimized. The corresponding mission time minimization problem is formulated as a coupled mixed-integer nonlinear program. For tractability, the original problem is decomposed into two subproblems respectively dealing with clustering-hovering optimization and intercluster UAV traveling path minimization. An alternating clustering-hovering optimization (ACH) and ant colony optimization (ACO) solution approach is proposed accordingly. Simulations are conducted to validate the superiority of the proposed ACH–ACO scheme over the scheme based on <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-means clustering.