TY - JOUR
T1 - Design and Performance Analysis of UAV-Assisted Maritime-LEO Satellite Communication Networks
AU - Senadhira, Nilupuli
AU - Durrani, Salman
AU - Guo, Jing
AU - Yang, Nan
AU - Zhou, Xiangyun
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2025
Y1 - 2025
N2 - Monitoring oceanic conditions via maritime Internet of Things (IoT) is vital to the health of the planet. In this regard, providing wireless connectivity to low-end ships, maritime buoys and beacons at sea, which typically lack the technology needed for direct satellite connections, remains a fundamental challenge given the vast ocean expanse and absence of any coverage from on-shore base stations (BSs). To address this challenge, we consider a uncrewed aerial vehicle (UAV)-assisted maritime low Earth orbit (LEO) satellite communication network to provide coverage for low-end maritime users (MUs), such as buoys in remote ocean regions. In this network, we assume that the MUs are distributed across a finite ocean area outside the coverage of onshore BSs. These MUs transmit data to satellites through a swarm of relay UAVs hovering in a finite aerial region, resulting in two communication phases: (i) MU-to-UAV and (ii) UAV-to-satellite. Leveraging stochastic geometry and UAV-centric analysis (which is different from conventional user-centric analysis) in the uplink, we analyze the location-dependent performance and derive an approximate yet accurate expression for the success probability, a key metric characterizing the overall MU-to-UAV-to-satellite network performance. Our numerical results demonstrate that given a set of satellite constellation parameters (e.g., number of satellites, altitude, and beamwidth), the success probability is governed by the interplay between path loss and interference. These results provide theoretical insights for the deployment and planning of integrated maritime-aerial-satellite networks to extend coverage for low-end MUs in remote ocean regions.
AB - Monitoring oceanic conditions via maritime Internet of Things (IoT) is vital to the health of the planet. In this regard, providing wireless connectivity to low-end ships, maritime buoys and beacons at sea, which typically lack the technology needed for direct satellite connections, remains a fundamental challenge given the vast ocean expanse and absence of any coverage from on-shore base stations (BSs). To address this challenge, we consider a uncrewed aerial vehicle (UAV)-assisted maritime low Earth orbit (LEO) satellite communication network to provide coverage for low-end maritime users (MUs), such as buoys in remote ocean regions. In this network, we assume that the MUs are distributed across a finite ocean area outside the coverage of onshore BSs. These MUs transmit data to satellites through a swarm of relay UAVs hovering in a finite aerial region, resulting in two communication phases: (i) MU-to-UAV and (ii) UAV-to-satellite. Leveraging stochastic geometry and UAV-centric analysis (which is different from conventional user-centric analysis) in the uplink, we analyze the location-dependent performance and derive an approximate yet accurate expression for the success probability, a key metric characterizing the overall MU-to-UAV-to-satellite network performance. Our numerical results demonstrate that given a set of satellite constellation parameters (e.g., number of satellites, altitude, and beamwidth), the success probability is governed by the interplay between path loss and interference. These results provide theoretical insights for the deployment and planning of integrated maritime-aerial-satellite networks to extend coverage for low-end MUs in remote ocean regions.
KW - LEO satellite networks
KW - Stochastic geometry
KW - UAVs
KW - maritime networks
UR - http://www.scopus.com/inward/record.url?scp=105005987256&partnerID=8YFLogxK
U2 - 10.1109/OJCOMS.2025.3571757
DO - 10.1109/OJCOMS.2025.3571757
M3 - Article
AN - SCOPUS:105005987256
SN - 2644-125X
VL - 6
SP - 4667
EP - 4688
JO - IEEE Open Journal of the Communications Society
JF - IEEE Open Journal of the Communications Society
ER -