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<p>To address the challenges of high path loss, sparse scatterer distribution, and surging system overhead caused by frequent beam handovers in high-frequency communications under complex dynamic wireless environments, we propose a mmWave radar-enabled reconfigurable intelligent surface (RIS) beamforming optimization method. By integrating environmental sensing with intelligent reflection control, a joint optimization framework is established to maximize the communication rate. The alternating direction method of multipliers (ADMM) is applied for distributed problem-solving, effectively reducing beamforming complexity in dynamic scenarios. First, the mmWave radar senses multi-user position information and transmits it to the RIS controller. Subsequently, the optimal phase configuration is calculated via the proposed optimization algorithm. Compared to traditional codebook-based search or fully connected beamforming architectures, the proposed sensing-communication co-design framework enhances adaptability to dynamic environments while reducing additional radio frequency (RF) chain overhead. Simulation results demonstrate the proposed method improves spectral efficiency by approximately 8 bps/Hz and 1 bps/Hz over random phase configuration methods and existing iterative optimization approaches, respectively.</p>

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Millimeter-wave radar-enabled multi-user beamforming optimization for reconfigurable intelligent surfaces

  • 期刊论文

  • 发表日期：

    2025年7月15日

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  • Wenyu Luo,
  • Yu Feng,
  • Jiahui Xu,
  • Chunyu Zhao,
  • Xia Shao,
  • Li Xu

摘要

To address the challenges of high path loss, sparse scatterer distribution, and surging system overhead caused by frequent beam handovers in high-frequency communications under complex dynamic wireless environments, we propose a mmWave radar-enabled reconfigurable intelligent surface (RIS) beamforming optimization method. By integrating environmental sensing with intelligent reflection control, a joint optimization framework is established to maximize the communication rate. The alternating direction method of multipliers (ADMM) is applied for distributed problem-solving, effectively reducing beamforming complexity in dynamic scenarios. First, the mmWave radar senses multi-user position information and transmits it to the RIS controller. Subsequently, the optimal phase configuration is calculated via the proposed optimization algorithm. Compared to traditional codebook-based search or fully connected beamforming architectures, the proposed sensing-communication co-design framework enhances adaptability to dynamic environments while reducing additional radio frequency (RF) chain overhead. Simulation results demonstrate the proposed method improves spectral efficiency by approximately 8 bps/Hz and 1 bps/Hz over random phase configuration methods and existing iterative optimization approaches, respectively.