TY - GEN
T1 - 3D Stochastic Geometry Model for Aerial Vehicle-Relayed Ground-Air-Satellite Connectivity
AU - Wang, Yulei
AU - Liu, Yalin
AU - Fu, Yaru
AU - Qin, Yujie
AU - Li, Zhongjie
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Due to their flexibility, aerial vehicles (AVs), such as unmanned aerial vehicles and airships, are widely employed as relays to assist communications between massive ground users (GUs) and satellites, forming an AV-relayed ground-air-satellite solution (GASS). In GASS, the deployment of AVs is crucial to ensure overall performance from GUs to satellites. This paper develops a stochastic geometry-based analytical model for GASS under Matérn hard-core point process (MHCPP) distributed AVs. The 3D distributions of AVs and GUs are modeled by considering their locations on spherical surfaces in the presence of high-altitude satellites. Accordingly, we derive an overall connectivity analytical model for GASS, which includes the average performance of AV-relayed two-hop transmissions. Extensive numerical results validate the accuracy of the connectivity model and provide essential insights for configuring AV deployments.
AB - Due to their flexibility, aerial vehicles (AVs), such as unmanned aerial vehicles and airships, are widely employed as relays to assist communications between massive ground users (GUs) and satellites, forming an AV-relayed ground-air-satellite solution (GASS). In GASS, the deployment of AVs is crucial to ensure overall performance from GUs to satellites. This paper develops a stochastic geometry-based analytical model for GASS under Matérn hard-core point process (MHCPP) distributed AVs. The 3D distributions of AVs and GUs are modeled by considering their locations on spherical surfaces in the presence of high-altitude satellites. Accordingly, we derive an overall connectivity analytical model for GASS, which includes the average performance of AV-relayed two-hop transmissions. Extensive numerical results validate the accuracy of the connectivity model and provide essential insights for configuring AV deployments.
KW - 3D stochastic geometry
KW - Matern hard-core point process (MHCPP)
KW - ground-air-satellite solution (GASS)
UR - https://www.scopus.com/pages/publications/105019054858
U2 - 10.1109/VTC2025-Spring65109.2025.11174375
DO - 10.1109/VTC2025-Spring65109.2025.11174375
M3 - Conference contribution
AN - SCOPUS:105019054858
T3 - IEEE Vehicular Technology Conference
BT - 2025 IEEE 101st Vehicular Technology Conference, VTC 2025-Spring 2025 - Proceedings
T2 - 101st IEEE Vehicular Technology Conference, VTC 2025-Spring
Y2 - 17 June 2025 through 20 June 2025
ER -