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UAV-Enabled Joint Sensing, Communication, Powering, and Backhaul Transmission in Maritime Monitoring Networks

  • Bohan Li
  • , Jiahao Liu
  • , Yujun Liang
  • , Qian Li
  • , Haochen Liu
  • , Yaoyuan Zhang
  • , Junsheng Mu*
  • , Shahid Mumtaz
  • , Sheng Chen
  • *Corresponding author for this work
  • Ocean University of China
  • Northwestern Polytechnical University Xian
  • Harbin Institute of Technology
  • Beijing University of Posts and Telecommunications
  • Nottingham Trent University

Research output: Contribution to journalArticlepeer-review

Abstract

This article addresses the challenge of energy-constrained maritime monitoring networks by proposing an uncrewed aerial vehicle (UAV)-enabled integrated sensing, communication, powering and backhaul (ISCPB) transmission scheme with a tailored time-division duplex frame structure. Within each time slot (TS), the UAV sequentially implements sensing, wireless charging and uplink receiving with buoys, and lastly forward part of collected data to the central ship via backhaul links. Considering the tight coupling among these functions, we jointly optimize time allocation, UAV trajectory, UAV-buoy association, and power scheduling to maximize the performance of data collection, with the practical consideration of sea clutter effects during UAV sensing. A novel optimization framework combining alternating optimization (AO), quadratic transform (QT), and augmented first-order Taylor approximation (A-FOTE) is developed, which demonstrates good convergence behavior and robustness. Simulation results show that under sensing quality-of-service (QoS) constraint, buoys are able to achieve an average data rate over 22 bps/Hz using around 2-mW harvested power per active TS, validating the scheme’s effectiveness for open-sea monitoring. Additionally, it is found that under the influence of sea clutters, the optimal UAV trajectory always keeps a certain distance with buoys to strike a balance between sensing and other multifunctional transmissions.

Original languageEnglish
Pages (from-to)7473-7486
Number of pages14
JournalIEEE Internet of Things Journal
Volume13
Issue number4
DOIs
StatePublished - 2026
Externally publishedYes

Keywords

  • Communication
  • integrated sensing
  • maritime monitoring network
  • powering and backhaul
  • sea clutter
  • uncrewed aerial vehicle (UAV)

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