A5037397916- Millimeter-Wave Propagation and Modeling
- Advanced MIMO Systems Optimization
- Full-Duplex Wireless Communications
- Wireless Signal Modulation Classification
- Advanced Wireless Communication Technologies
Southeast University
2022-2023
Purple Mountain Laboratories
2022-2023
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...
Precoding design exploiting deep learning methods has been widely studied for multiuser multiple-input multiple-output (MU-MIMO) systems. However, conventional neural precoding applies black-box-based networks which are less interpretable. In this letter, we propose a learning-based method based on an interpretable of network, namely iPNet. particular, the iPNet mimics classic minimum mean-squared error (MMSE) and approximates matrix inversion in network architecture. Specifically, proposed...
Due to the ability of feature extraction, deep learning (DL)-based methods have been recently applied channel state information (CSI) compression feedback in massive multiple-input multiple-output (MIMO) systems. Existing DL-based CSI are usually effective extracting a certain type features CSI. However, contains two types propagation features, i.g., non-line-of-sight (NLOS) propagation-path and dominant feature, especially environments with rich scatterers. To fully extract both learn...