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Your search keyword '"Cao, Hailin"' showing total 242 results
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242 results on '"Cao, Hailin"'

26. Magnitude‐Controlled Phase Based on Euler's Formula.

Author

Sun, Zhiwei, Sima, Boyu, Xu, Ruolei, He, Bo, Cao, Hailin, Zhao, Junming, and Feng, Yijun

Subjects
HALL effect, HOLOGRAPHY, PHASE modulation, DIGITAL holographic microscopy, ACOUSTICS, OPTICS, ANGULAR momentum (Mechanics)
Abstract

Phase manipulation plays a fundamental role in electromagnetic (EM) and optics research, i.e., the wavefront shaping depends heavily on phase modulation. However, the previous phase manipulation methods are limited to phase‐angle dimensionality, and the magnitude and phase are generally deemed as two distinct characters that should be controlled separately. Herein, a phase manipulation method in which phase is modulated by magnitude is proposed that follows an EM expression of Euler's formula. A rotation phase of linearly‐polarized waves is presented. Using this method, several unique applications in this research are demonstrated. First, a Hall effect of non‐angular‐momentum waves is obtained; second, an interdigital topology model with a unique topological‐charge control strategy is presented; and finally, the method is applied to holographic imaging, of which information of the hologram is recorded as a distribution of magnitude. Furthermore, as this method is applicable to all forms of harmonic waves, it can be potentially applied to other areas of wave phenomena such as acoustics and mechanics. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Optimized Nitrogen Fertilizer Rate Can Increase Yield and Nitrogen Use Efficiency for Open-Field Chinese Cabbage in Southwest China

Author

Cao, Hailin, primary, Zhang, Fen, additional, Fu, Jian, additional, Ma, Xiao, additional, Wang, Junjie, additional, Liu, Fabo, additional, Guo, Guangzheng, additional, Tian, Yiming, additional, Liang, Tao, additional, Zhou, Na, additional, Wang, Yan, additional, Chen, Xinping, additional, and Wang, Xiaozhong, additional

Published
2023
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31. Active RIS-Assisted Sup-Degree of Freedom Interference Suppression for a Large Antenna Array: A Deep-Learning Approach With Location Awareness

Author

Zhang, Zhengjie, Cao, Hailin, Fan, Jin, Peng, Junhui, and Liu, Sheng

Abstract

Radio frequency interference (RFI) generated by satellites orbiting the Earth has become a significant threat to astronomical observations. Active reconfigurable intelligent surfaces (RISs) have the capacity to intelligently control the wireless propagation environment and compensate for double-path fading attenuation. Thus, this article exploits an active RIS to mitigate RFI by forming an additional path to reflect RFI. Specifically, the model provides a new solution to sup-degree of freedom (DoF) interference suppression, which means that the amount of interferences surpasses the array DoF. We intend to simultaneously design the receive beamforming of large antenna array and reflection coefficients of active RIS to maximize the received signal-to-interference-plus-noise ratio (SINR). Moreover, the system model can be correlated with a non-Euclidean graph structure due to its graph-like nature. To achieve this objective, a deep-learning (DL) approach, named the location awareness graph ordering attention (LAGOAT) network, is presented to map the locations of RFI and array into the receive beamforming and reflection coefficients. The simulations not only demonstrate that our proposed system can improve significantly the received SINR but also show that proposed LAGOAT network can achieve superior performance compared with other DL approaches, namely, graph neural network (GNN), graph attention network (GAT), and the network without GOAT.

Published
2024
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32. Decentralized Federated Learning for Secure Space-Terrestrial Communication With Intelligent Reflecting Surface

Author

Cao, Hailin, Feng, Wenjuan, He, Jialuo, and Liu, Sheng

Abstract

Decentralized federated learning (DFL) is viewed as a promising distributed machine learning technique for developing models for wireless networks in order to protect user privacy and reduce communication traffic. In this letter, we propose a DFL framework aided by intelligent reflecting surface (IRS) for aerial-terrestrial integrated networks without a central server. The parameters of the trained model are then transmitted to the satellite. IRS is utilized to reconfigure the wireless propagation environment in order to maximize resource utilization. In this system, we devise a secrecy rate maximization problem with a time-consuming analysis and propose an alternative optimization for configuring the parameters cooperatively. The simulation results show that the proposed algorithm is effective in the IRS-assisted DFL system and can outperform the SDP algorithm by up to 20%.

Published
2023
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