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Reconfigurable intelligent surface and UAV coordination for reliable THz wireless networks.

M Rudra Kumar1, Ravi Uyyala2, M Ramchander3

  • 1Department of Information Technology, Mahatma Gandhi Institute of Technology, Hyderabad, Telangana, India.

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This study introduces a RIS-assisted UAV positioning framework to improve Terahertz (THz) communications by optimizing reconfigurable intelligent surfaces (RIS) and unmanned aerial vehicles (UAVs) for better reliability and data rates.

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Area of Science:

  • Wireless communication systems
  • Next-generation wireless networks
  • Terahertz (THz) communication

Background:

  • Terahertz (THz) communication offers ultra-high data rates for future wireless networks.
  • Challenges include severe path loss, molecular absorption, and blockage sensitivity, limiting coverage and reliability.

Purpose of the Study:

  • To propose a Reconfigurable Intelligent Surface (RIS)-assisted Unmanned Aerial Vehicle (UAV) positioning (RAVP) framework.
  • To enhance Terahertz (THz) communication performance by jointly optimizing RIS configuration and UAV deployment.

Main Methods:

  • Integration of RIS for controllable signal reflection and UAVs for flexible RIS placement.
  • A reinforcement learning (RL)-based strategy combining modified K-means clustering and gradient-based optimization.
  • Coordinated optimization of user grouping, RIS phase-shift, and UAV positioning.

Main Results:

  • Consistent improvements in link robustness, achievable data rate, and user connectivity.
  • Demonstrated performance gains compared to conventional THz systems without RIS or UAV optimization.
  • Effective coordination of RIS and UAVs enhances overall communication performance.

Conclusions:

  • The proposed RIS-UAV coordinated optimization framework significantly enhances THz communication.
  • Highlights the potential for 6G-enabled applications like smart cities and the Internet of Things (IoT).
  • Coordinated RIS-UAV deployment is crucial for overcoming THz communication limitations.