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ZHONG Weizhi, WAN Shiqing, DUAN Hongtao, FAN Zhenxiong, LIN Zhipeng, HUANG Yang, MAO Kai. A Joint Beamforming Method Based on Cooperative Co-evolutionary in Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle Communication System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240561
Citation: ZHONG Weizhi, WAN Shiqing, DUAN Hongtao, FAN Zhenxiong, LIN Zhipeng, HUANG Yang, MAO Kai. A Joint Beamforming Method Based on Cooperative Co-evolutionary in Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle Communication System[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240561

A Joint Beamforming Method Based on Cooperative Co-evolutionary in Reconfigurable Intelligent Surface-Assisted Unmanned Aerial Vehicle Communication System

doi: 10.11999/JEIT240561
Funds:  The National Natural Science Foundation of China (62271250), The Key Technologies R&D Program of Jiangsu (Prospective and Key Technologies for Industry) (BE2022067, BE2022067-1, BE2022067-3), Postgraduate Research and Practice Innovation Program of Nanjing University of Aeronautics and Astronautics (xcxjh20231507)
  • Received Date: 2024-07-04
  • Rev Recd Date: 2024-11-08
  • Available Online: 2024-11-13
  • Considering the limitations of traditional joint beamforming methods in optimizing Reconfigurable Intelligent Surface (RIS)-assisted Unmanned Aerial Vehicle (UAV) communication systems, such as solely focusing on the phase shift matrix optimization of RIS and the lack of universality in the optimization approach, a joint beamforming method based on Cooperative Co-Evolutionary Algorithm (CCEA) for the RIS-assisted UAV multi-user communication system is proposed. This method decomposes the joint beamforming problem into subproblems involving RIS reflection beam design and transmitter beam design, which are solved through information exchange and collaboration during the independent evolutionary process of two subpopulations. Simulation results demonstrate that compared to joint beamforming optimization only considering RIS phase shift matrix design, CCEA changes the energy distribution of the reflection wave in three-dimensional space by optimizing the RIS reflection wave shape, leading to improved reception-side signal-to-interference-plus-noise ratio (SINR) and spectral efficiency. Additionally, CCEA generates more diverse solutions that effectively cover user directions at various UAV and user positions, avoiding local optima and exhibiting greater applicability across different scenarios compared to traditional methods.
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