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<p>To address the issue of excessive communication system overhead caused by high path loss, low scattering, and frequent switching of high-frequency band communication in complex dynamic wireless environments, this paper proposes a power control method for reconfigurable intelligent surface (RIS)-assisted wireless communication systems based on frequency-modulated continuous wave (FMCW) radar sensing of location information. By integrating dynamic user location information obtained from FMCW radar with RIS technology, the proposed method reduces the additional overhead caused by user location uncertainty. Furthermore, a stochastic geometric channel model is established to more accurately simulate real-world complex environments by considering the impact of multipath effects on system gain. Based on this, an upper bound for the system outage probability is derived, and a binary search algorithm-based power optimization method is proposed to optimize the base station transmission power while adhering to the constraints of the communication system. Simulation results demonstrate that, compared to baseline methods, the proposed approach reduces the minimum required base station transmission power by 3.6–4&#xa0;dB and improves the system outage probability by approximately 38.5%.</p>

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Power control scheme of reconfigurable intelligent surface-assisted wireless communication system based on millimeter-wave radar

  • 期刊论文

  • 发表日期：

    2025年7月3日

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  • Luo Wenyu,
  • Xuan Annan,
  • Yan Tianze,
  • Shao Xia

摘要

To address the issue of excessive communication system overhead caused by high path loss, low scattering, and frequent switching of high-frequency band communication in complex dynamic wireless environments, this paper proposes a power control method for reconfigurable intelligent surface (RIS)-assisted wireless communication systems based on frequency-modulated continuous wave (FMCW) radar sensing of location information. By integrating dynamic user location information obtained from FMCW radar with RIS technology, the proposed method reduces the additional overhead caused by user location uncertainty. Furthermore, a stochastic geometric channel model is established to more accurately simulate real-world complex environments by considering the impact of multipath effects on system gain. Based on this, an upper bound for the system outage probability is derived, and a binary search algorithm-based power optimization method is proposed to optimize the base station transmission power while adhering to the constraints of the communication system. Simulation results demonstrate that, compared to baseline methods, the proposed approach reduces the minimum required base station transmission power by 3.6–4 dB and improves the system outage probability by approximately 38.5%.