516 citations · 1.7k across the 101 of their papers we have counts for
12 papers · 1 filter
FusionNet: Enhanced Beam Prediction for mmWave Communications Using Sub-6GHz Channel and A Few Pilots
Chenghong Bian, Yuwen Yang, Feifei Gao +1
In this paper, we propose a new downlink beamforming strategy for mmWave communications using uplink sub-6GHz channel information and a very few mmWave pilots. Specifically, we des…
Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO
Yindi Yang, Shun Zhang, Feifei Gao +3
In massive multiple-input multiple-output (MIMO) systems, the large number of antennas would bring a great challenge for the acquisition of the accurate channel state information,…
Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication
Shunbo Zhang, Shun Zhang, Feifei Gao +2
To capture the communications gain of the massive radiating elements with low power cost, the conventional reconfigurable intelligent surface (RIS) usually works in passive mode. H…
Deep Multimodal Learning: Merging Sensory Data for Massive MIMO Channel Prediction
Yuwen Yang, Feifei Gao, Chengwen Xing +2
Existing work in intelligent communications has recently made preliminary attempts to utilize multi-source sensing information (MSI) to improve the system performance. However, the…
Graph Neural Network based Channel Tracking for Massive MIMO Networks
Yindi Yang, Shun Zhang, Feifei Gao +2
In this paper, we resort to the graph neural network (GNN) and propose the new channel tracking method for the massive multiple-input multiple-output networks under the high mobili…
Deep Learning based Denoise Network for CSI Feedback in FDD Massive MIMO Systems
Hongyuan Ye, Feifei Gao, Jing Qian +2
Channel state information (CSI) feedback is critical for frequency division duplex (FDD) massive multi-input multi-output (MIMO) systems. Most conventional algorithms are based on…