1 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
Energy-Efficient Hybrid Beamfocusing for Near-Field Integrated Sensing and Communication
Wenhao Hu, Zhenyao He, Wei Xu +3
Integrated sensing and communication (ISAC) is a pivotal component of sixth-generation (6G) wireless networks, leveraging high-frequency bands and massive multiple-input multiple-o…
Generative Learning Powered Probing Beam Optimization for Cell-Free Hybrid Beamforming
Cheng Zhang, Shuangbo Xiong, Mengqing He +3
Probing beam measurement (PBM)-based hybrid beamforming provides a feasible solution for cell-free MIMO. In this letter, we propose a novel probing beam optimization framework wher…
Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks
Chunmei Xu, Shengheng Liu, Yongming Huang +2
At present, there is a trend to deploy ubiquitous artificial intelligence (AI) applications at the edge of the network. As a promising framework that enables secure edge intelligen…
Entropy-based Probing Beam Selection and Beam Prediction via Deep Learning
Fan Meng, Cheng Zhang, Yongming Huang +3
Hierarchical beam search in mmWave communications incurs substantial training overhead, necessitating deep learning-enabled beam predictions to effectively leverage channel priors…
Traffic-Aware Hierarchical Beam Selection for Cell-Free Massive MIMO
Chenyang Wang, Cheng Zhang, Fan Meng +2
Beam selection for joint transmission in cell-free massive multi-input multi-output systems faces the problem of extremely high training overhead and computational complexity. The…