
Design and Performance Analysis of UAV-Assisted Maritime-LEO Satellite Communication Networks
Author(s) -
Nilupuli Senadhira,
Salman Durrani,
Jing Guo,
Nan Yang,
Xiangyun Zhou
Publication year - 2025
Publication title -
ieee open journal of the communications society
Language(s) - English
Resource type - Magazines
eISSN - 2644-125X
DOI - 10.1109/ojcoms.2025.3571757
Subject(s) - communication, networking and broadcast technologies
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 unmanned 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.
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