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Unmanned aerial vehicle (UAV)-aided maritime communication networks (MCNs) face low throughput and transmission efficiency challenges. We first characterize a millimeter wave (mmWave) UAV-aided MCN to enhance network performance and implement dynamic beam management to address device mobility and time-varying channels. We propose a small-timescale mmWave beamforming sub-problem utilizing a normalized least mean square adaptable beamforming scheme to capacity maximization alongside a large-timescale beam tracking sub-problem that integrates a Kalman filter for state prediction and a non-blind minimum variance distortionless response algorithm for beam reconstruction. Numerical results demonstrate the effectiveness of mmWave beamforming in enhancing capacity, improving mobility prediction, and optimizing joint dynamic beam management.

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mmWave-Based High-Capacity Beam Management in UAV-Aided Maritime Communication Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Xueyan Cao,
  • Jun Cui,
  • Fei Xu

摘要

Unmanned aerial vehicle (UAV)-aided maritime communication networks (MCNs) face low throughput and transmission efficiency challenges. We first characterize a millimeter wave (mmWave) UAV-aided MCN to enhance network performance and implement dynamic beam management to address device mobility and time-varying channels. We propose a small-timescale mmWave beamforming sub-problem utilizing a normalized least mean square adaptable beamforming scheme to capacity maximization alongside a large-timescale beam tracking sub-problem that integrates a Kalman filter for state prediction and a non-blind minimum variance distortionless response algorithm for beam reconstruction. Numerical results demonstrate the effectiveness of mmWave beamforming in enhancing capacity, improving mobility prediction, and optimizing joint dynamic beam management.