activity
20192022
most citedDeep Learning based Channel Estimation for Massive MIMO with Hybrid Transceivers

29 citations · 50 across the 7 of their papers we have counts for

collaborators

8 papers

cs.IT2022

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…

cs.IT20221 cited

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…

cs.IT2022

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…

cs.IT202229 cited

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…

cs.IT20216 cited

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)…

cs.IT2020

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…