Throughput Optimization for Multi-UAV-Assisted Offshore Internet of Things: A Hypergraph Approach

Abstract

The rapid growth of marine applications leads to a significant increase in Maritime Devices (MDs). Traditional shore-based maritime communication networks face limitations, such as overloaded and transmission distance to provide network services for MDs. Unmanned Aerial Vehicles (UAVs) act as relays that can expand coverage and enhance the quality of service for offshore communication networks. We consider a multi-UAV-assisted Offshore Internet of Things (mUAV-OloT), and formulate a throughput maximization problem by jointly optimizing channel allocation, Leader MD (LMD) selection, UAV-LMD association, and LMD-MD association. Firstly, we propose the Hypergraph-based Two-Stage Matching (HTSM) algorithm where a Hypergraph-based LMD Selection (HLMDS) strategy is employed to identify the set of LMDs. Secondly, the Kuhn-Munkres algorithm is used to optimize the UAV-LMD association and a Weighted Three-dimensional Hypergraph Matching (WTHM) algorithm is designed to solve the LMD-MD association and channel allocation. Numerical results show that the HTSM algorithm outperforms benchmark algorithms regarding throughput.