A5026685727- Millimeter-Wave Propagation and Modeling
- Wireless Signal Modulation Classification
- Orbital Angular Momentum in Optics
- Speech and Audio Processing
- Optical Wireless Communication Technologies
- Cell Image Analysis Techniques
- Sperm and Testicular Function
- Advanced Fluorescence Microscopy Techniques
- Image Processing Techniques and Applications
- Quantum Information and Cryptography
- Random lasers and scattering media
- Advanced MIMO Systems Optimization
Jiangnan University
2023
Southeast University
2022-2023
Purple Mountain Laboratories
2022
In order to fully exploit the advantages of massive multiple-input multiple-output (mMIMO), it is critical for transmitter accurately acquire channel state information (CSI). Deep learning (DL)-based methods have been proposed CSI compression and feedback transmitter. Although most existing DL-based consider matrix as an image, structural features image are rarely exploited in neural network design. As such, we propose a model self-information that dynamically measures amount contained each...
Abstract We investigate the impacts of backward scattering (BS) non-Kolmogorov turbulence on entangled perfect Laguerre–Gaussian (PLG) beams. The explicit expressions for PLG quantum entanglement and coherence are derived in BS case. find that introduction reduces coherence, disrupts initial decay characteristics, induces revival which sense may possess a non-Markovian (memory) effect. As OAM number increases, feature increases logarithmically. In addition, universal effects also explored.
Deep learning (DL)-based channel state information (CSI) feedback methods compressed the CSI matrix by exploiting its delay and angle features straightforwardly, while measure in terms of contained has rarely been considered. Based on this observation, we introduce self-information as an informative representation from perspective theory, which reflects amount original explicit way. Then, a novel DL-based network is proposed for temporal compression domain, namely SD-CsiNet. The SD-CsiNet...
Transmission electron microscopy (TEM) image drift correction has been effectively addressed using diverse approaches, including the cross correlation algorithm (CC) and other strategies. However, most of strategies fall short achieving sufficient accuracy or cannot strike a balance between time consumption accuracy. The present study proposes TEM strategy that enhances without any additional consumption. Unlike CC matches pixels one by one, our approach involves extraction multiple feature...
Deep learning (DL)-based channel state information (CSI) feedback methods compressed the CSI matrix by exploiting its delay and angle features straightforwardly, while measure in terms of contained has rarely been considered. Based on this observation, we introduce self-information as an informative representation from perspective theory, which reflects amount original explicit way. Then, a novel DL-based network is proposed for temporal compression domain, namely SD-CsiNet. The SD-CsiNet...