IEEE transactions on wireless communications2025,Vol.24Issue(11) :8925-8938.DOI:10.1109/TWC.2025.3569840

Online Adaptive Real-Time Beamforming Design for Dynamic Environments in Cell-Free Systems

Guanghui Chen Zheng Wang Hongxin Lin Pengguang Du Yongming Huang
IEEE transactions on wireless communications2025,Vol.24Issue(11) :8925-8938.DOI:10.1109/TWC.2025.3569840

Online Adaptive Real-Time Beamforming Design for Dynamic Environments in Cell-Free Systems

Guanghui Chen 1Zheng Wang 2Hongxin Lin 3Pengguang Du 2Yongming Huang1
扫码查看

作者信息

  • 1. School of Information Science and Engineering and the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China|Pervasive Communications Center, Purple Mountain Laboratories, Nanjing, China
  • 2. School of Information Science and Engineering and the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China
  • 3. Purple Mountain Laboratories, Nanjing, China
  • 折叠

Abstract

In this paper, we consider real-time beamforming design for dynamic wireless environments with varying channels and different numbers of access points (APs) and users in cell-free systems. Specifically, a sum spectral efficiency (SE) maximization optimization problem is formulated for the beamforming design in dynamic wireless environments of cell-free systems. To efficiently solve it, a high-generalization network (HGNet) is proposed to adapt to the changing numbers of APs and users. Then, a high-generalization beamforming module is also designed in HGNet to extract the valuable features for the varying channels, and we theoretically prove that such a high-generalization beamforming module is able to reduce the upper bound of the generalization error. Subsequently, by online adaptively updating about 3% of the parameters of HGNet, an online adaptive updating (OAU) algorithm is proposed to enable the online adaptive real-time beamforming design for improving the sum SE. Numerical results demonstrate that the proposed HGNet with OAU algorithm achieves a higher sum SE with a lower computational cost on the order of milliseconds.

Key words

Array signal processing/Wireless communication/Real-time systems/Heuristic algorithms/Deep learning/Optimization/Training/Computational efficiency/Vehicle dynamics/Upper bound

引用本文复制引用

出版年

2025
IEEE transactions on wireless communications

IEEE transactions on wireless communications

ISSN:
参考文献量39
段落导航相关论文