π€ AI Summary
This study addresses the asymptotic distribution of two critical transmission radii in three-dimensional random geometric graphs: one defined by $k$-connectivity and the other by minimum vertex degree. Existing theory lacks precise asymptotic characterizations for the 3D case. To bridge this gap, we model node deployment via a spatial Poisson point process and employ rigorous probabilistic analysis combined with extreme-value asymptotics. We derive, for the first time, the exact asymptotic distributions of both radii under the high-density limitβboth converge to the Gumbel extreme-value distribution, with explicitly characterized centering and scaling constants. This result reveals the fine-grained structure of the connectivity phase transition in 3D wireless networks and establishes, for the first time, the asymptotic equivalence between the $k$-connectivity and minimum-degree thresholds in three dimensions. The findings provide foundational theoretical support and principled guidelines for topology-aware design and parameter selection in 3D sensor networks and UAV communication systems.
π Abstract
This article presents the precise asymptotical distribution of two types of critical transmission radii, defined in terms of k-connectivity and the minimum vertex degree, for random geometry graphs distributed over three-dimensional regions.