{"ID":2896178,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.07832","arxiv_id":"2507.07832","title":"Flying Base Stations for Offshore Wind Farm Monitoring and Control: Holistic Performance Evaluation and Optimization","abstract":"Ensuring reliable and low-latency communication in offshore wind farms is critical for efficient monitoring and control, yet remains challenging due to the harsh environment and lack of infrastructure. This paper investigates a flying base station (FBS) approach for wide-area monitoring and control in the UK Hornsea offshore wind farm project. By leveraging mobile, flexible FBS platforms in the remote and harsh offshore environment, the proposed system offers real-time connectivity for turbines without the need for deploying permanent infrastructure at the sea. We develop a detailed and practical end-to-end latency model accounting for five key factors: flight duration, connection establishment, turbine state information upload, computational delay, and control transmission, to provide a holistic perspective often missing in prior studies. Furthermore, we combine trajectory planning, beamforming, and resource allocation into a multi-objective optimization framework for the overall latency minimization, specifically designed for large-scale offshore wind farm deployments. Simulation results verify the effectiveness of our proposed method in minimizing latency and enhancing efficiency in FBS-assisted offshore monitoring across various power levels, while consistently outperforming baseline designs.","short_abstract":"Ensuring reliable and low-latency communication in offshore wind farms is critical for efficient monitoring and control, yet remains challenging due to the harsh environment and lack of infrastructure. This paper investigates a flying base station (FBS) approach for wide-area monitoring and control in the UK Hornsea of...","url_abs":"https://arxiv.org/abs/2507.07832","url_pdf":"https://arxiv.org/pdf/2507.07832v1","authors":"[\"Xinyi Lin\",\"Peizheng Li\",\"Adnan Aijaz\"]","published":"2025-07-10T15:03:52Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}