7 citations · 11 across the 5 of their papers we have counts for
5 papers
Deep Learning for 1-Bit Compressed Sensing-based Superimposed CSI Feedback
Chaojin Qing, Qing Ye, Bin Cai +2
In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, 1-bit compressed sensing (CS)-based superimposed channel state information (CSI) feedba…
ELM-based Superimposed CSI Feedback for FDD Massive MIMO System
Chaojin Qing, Bin Cai, Qingyao Yang +2
In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO), deep learning (DL)-based superimposed channel state information (CSI) feedback has presented pr…
ELM-based Frame Synchronization in Burst-Mode Communication Systems with Nonlinear Distortion
Chaojin Qing, Wang Yu, Bin Cai +2
In burst-mode communication systems, the quality of frame synchronization (FS) at receivers significantly impacts the overall system performance. To guarantee FS, an extreme learni…
Superimposed Coding Based CSI Feedback Using 1-Bit Compressed Sensing
Chaojin Qing, Qingyao Yang, Bin Cai +2
In a frequency division duplex (FDD) massive multiple input multiple output (MIMO) system, the channel state information (CSI) feedback causes a significant bandwidth resource occu…
Deep Learning for CSI Feedback Based on Superimposed Coding
Chaojin Qing, Bin Cai, Qingyao Yang +2
Massive multiple-input multiple-output (MIMO) with frequency division duplex (FDD) mode is a promising approach to increasing system capacity and link robustness for the fifth gene…