29 citations · 50 across the 12 of their papers we have counts for
12 papers
Deep Unfolding-Based Channel Estimation for Wideband TeraHertz Near-Field Massive MIMO Systems
Jiabao Gao, Xiaoming Cheng, Geoffrey Ye Li
The combination of Terahertz (THz) and massive multiple-input multiple-output (MIMO) is promising to meet the increasing data rate demand of future wireless communication systems t…
AMP-SBL Unfolding for Wideband MmWave Massive MIMO Channel Estimation
Jiabao Gao, Caijun Zhong, Geoffrey Ye Li
In wideband millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, channel estimation is challenging due to the hybrid analog-digital architecture, which c…
Spatially Sparse Precoding in Wideband Hybrid Terahertz Massive MIMO Systems
Jiabao Gao, Caijun Zhong, Geoffrey Ye Li +2
In terahertz (THz) massive multiple-input multiple-output (MIMO) systems, the combination of huge bandwidth and massive antennas results in severe beam split, thus making the conve…
Learn to Adapt to New Environment from Past Experience and Few Pilot
Ouya Wang, Jiabao Gao, Geoffrey Ye Li
In recent years, deep learning has been widely applied in communications and achieved remarkable performance improvement. Most of the existing works are based on data-driven deep l…
A Deep Learning-Based Framework for Low Complexity Multi-User MIMO Precoding Design
Maojun Zhang, Jiabao Gao, Caijun Zhong
Using precoding to suppress multi-user interference is a well-known technique to improve spectra efficiency in multiuser multiple-input multiple-output (MU-MIMO) systems, and the p…
Deep Learning-based Channel Estimation for Wideband Hybrid MmWave Massive MIMO
Jiabao Gao, Caijun Zhong, Geoffrey Ye Li +2
Hybrid analog-digital (HAD) architecture is widely adopted in practical millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems to reduce hardware cost and e…
Online Deep Neural Network for Optimization in Wireless Communications
Jiabao Gao, Caijun Zhong, Geoffrey Ye Li +1
Recently, deep neural network (DNN) has been widely adopted in the design of intelligent communication systems thanks to its strong learning ability and low testing complexity. How…
Deep Learning based Channel Estimation for Massive MIMO with Hybrid Transceivers
Jiabao Gao, Caijun Zhong, Geoffrey Ye Li +1
Accurate and efficient estimation of the high dimensional channels is one of the critical challenges for practical applications of massive multiple-input multiple-output (MIMO). In…
An Attention-Aided Deep Learning Framework for Massive MIMO Channel Estimation
Jiabao Gao, Mu Hu, Caijun Zhong +2
Channel estimation is one of the key issues in practical massive multiple-input multiple-output (MIMO) systems. Compared with conventional estimation algorithms, deep learning (DL)…
Deep Reinforcement Learning for Joint Beamwidth and Power Optimization in mmWave Systems
Jiabao Gao, Caijun Zhong, Xiaoming Chen +2
This paper studies the joint beamwidth and transmit power optimization problem in millimeter wave communication systems. A deep reinforcement learning based approach is proposed. S…
Unsupervised Learning for Passive Beamforming
Jiabao Gao, Caijun Zhong, Xiaoming Chen +2
Reconfigurable intelligent surface (RIS) has recently emerged as a promising candidate to improve the energy and spectral efficiency of wireless communication systems. However, the…
Deep Learning for Spectrum Sensing
Jiabao Gao, Xuemei Yi, Caijun Zhong +2
In cognitive radio systems, the ability to accurately detect primary user's signal is essential to secondary user in order to utilize idle licensed spectrum. Conventional energy de…