1 citations · 1 across the 5 of their papers we have counts for
7 papers
Co-learning-aided Multi-modal-deep-learning Framework of Passive DOA Estimators for a Heterogeneous Hybrid Massive MIMO Receiver
Jiatong Bai, Feng Shu, Qinghe Zheng +5
Due to its excellent performance in rate and resolution, fully-digital (FD) massive multiple-input multiple-output (MIMO) antenna arrays has been widely applied in data transmissio…
Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning
Qiankun Cheng, Jiatong Bai, Baihua Shi +2
This paper models an active intelligent reflecting surface (IRS) -assisted wireless communication network, which has the ability to adjust power between BS and IRS. We aim to maxim…
A New Heterogeneous Hybrid Massive MIMO Receiver with An Intrinsic Ability of Removing Phase Ambiguity of DOA Estimation via Machine Learning
Feng Shu, Baihua Shi, Yiwen Chen +5
Massive multiple input multiple output (MIMO) antenna arrays eventuate a huge amount of circuit costs and computational complexity. To satisfy the needs of high precision and low c…
Deep Learning Based DOA Estimation for Hybrid Massive MIMO Receive Array with Overlapped Subarrays
Yifan Li, Baihua Shi, Feng Shu +2
To improve the accuracy of direction-of-arrival (DOA) estimation, a deep learning (DL)-based method called CDAE-DNN is proposed for hybrid analog and digital (HAD) massive MIMO rec…
High-performance Passive Eigen-model-based Detectors of Single Emitter Using Massive MIMO Receivers
Qijuan Jie, Xichao Zhan, Feng Shu +4
For a passive direction of arrival (DoA) measurement system using massive multiple input multiple output (MIMO), it is mandatory to infer whether the emitter exists or not before p…
Fast Ambiguous DOA Elimination Method of DOA Measurement for Hybrid Massive MIMO Receiver
Nuo Chen, Xinyi Jiang, Baihua Shi +6
DOA estimation for massive multiple-input multiple-output (MIMO) system can provide ultra-high-resolution angle estimation. However, due to the high computational complexity and co…