19 citations · 28 across the 12 of their papers we have counts for
11 papers · 1 filter
DNN-based Enhanced DOA Sensing via Massive MIMO Receiver with Switches-based Hybrid Architecture
Yifan Li, Kang Wei, Linqiong Jia +4
Switches-based hybrid architecture has attracted much attention, especially in directional-of-arrival (DOA) sensing, due to its ability of significantly reducing the hardware cost…
Machine Learning-based Near-field Emitter Location Sensing via Grouped Hybrid Analog and Digital XL-MIMO Receive Array
Jiatong Bai, Yifan Li, Feng Shu +5
As a green MIMO structure, the partially-connected hybrid analog and digital (PC-HAD) structure has been widely used in the far-field (FF) scenario for it can significantly reduce…
A Novel Tree Model-based DNN to Achieve a High-Resolution DOA Estimation via Massive MIMO receive array
Yifan Li, Feng Shu, Jun Zou +3
To satisfy the high-resolution requirements of direction-of-arrival (DOA) estimation, conventional deep neural network (DNN)-based methods using grid idea need to significantly inc…
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…
Low-Complexity Three-Dimensional AOA-Cross Geometric Center Localization Methods via Multi-UAV network
Baihua Shi, Yifan Li, Guilu Wu +2
Angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of ar…
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…
Optimal Measurement of Drone Swarm in RSS-based Passive Localization with Region Constraints
Xin Cheng, Feng Shu, Yifan Li +3
Passive geolocation by multiple unmanned aerial vehicles (UAVs) covers a wide range of military and civilian applications including rescue, wild life tracking and electronic warfar…
Rapid Phase Ambiguity Elimination Methods for DOA Estimator via Hybrid Massive MIMO Receive Array
Xichao Zhan, Yiwen Chen, Feng Shu +5
For a sub-connected hybrid multiple-input multiple-output (MIMO) receiver with subarrays and antennas, there exists a challenging problem of how to rapidly remove phase amb…
Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array
Yifan Li, Feng Shu, Jinsong Hu +6
To provide important prior knowledge for the DOA estimation of UAV emitters in future wireless networks, we present a complete DOA preprocessing system for inferring the number of…
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…
Enhanced RSS-based UAV Localization via Trajectory and Multi-base Stations
Yifan Li, Feng Shu, Baihua Shi +3
To improve the localization precision of unmanned aerial vehicle (UAV), a novel framework is established by jointly utilizing multiple measurements of received signal strength (RSS…