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Cited by
Year
3GPP TR 38.901 channel model
Q Zhu, CX Wang, B Hua, K Mao, S Jiang, M Yao
the wiley 5G Ref: the essential 5G reference online, 1-35, 2021
1502021
A UAV-aided real-time channel sounder for highly dynamic nonstationary A2G scenarios
K Mao, Q Zhu, Y Qiu, X Liu, M Song, W Fan, ABJ Kokkeler, Y Miao
IEEE transactions on instrumentation and measurement 72, 1-15, 2023
1382023
A novel 3D non-stationary wireless MIMO channel simulator and hardware emulator
Q Zhu, H Li, Y Fu, CX Wang, Y Tan, X Chen, Q Wu
IEEE Transactions on Communications 66 (9), 3865-3878, 2018
1362018
A survey on channel sounding technologies and measurements for UAV-assisted communications
K Mao, Q Zhu, CX Wang, X Ye, J Gomez-Ponce, X Cai, Y Miao, Z Cui, ...
IEEE Transactions on Instrumentation and Measurement, 2024
1052024
Channel modeling for UAV-to-ground communications with posture variation and fuselage scattering effect
B Hua, H Ni, Q Zhu, CX Wang, T Zhou, K Mao, J Bao, X Zhang
IEEE Transactions on Communications 71 (5), 3103-3116, 2023
1002023
Sparse Bayesian learning-based 3-D radio environment map construction—Sampling optimization, scenario-dependent dictionary construction, and sparse recovery
J Wang, Q Zhu, Z Lin, Q Wu, Y Huang, X Cai, W Zhong, Y Zhao
IEEE transactions on cognitive communications and networking 10 (1), 80-93, 2023
912023
Machine-learning-based 3-D channel modeling for U2V mmWave communications
K Mao, Q Zhu, M Song, H Li, B Ning, GF Pedersen, W Fan
IEEE Internet of Things Journal 9 (18), 17592-17607, 2022
882022
A novel 3D non-stationary UAV-MIMO channel model and its statistical properties
Q Zhu, K Jiang, X Chen, W Zhong, Y Yang
China Communications 15 (12), 147-158, 2018
872018
Sparse Bayesian learning-based hierarchical construction for 3D radio environment maps incorporating channel shadowing
J Wang, Q Zhu, Z Lin, J Chen, G Ding, Q Wu, G Gu, Q Gao
IEEE Transactions on Wireless Communications 23 (10), 14560-14574, 2024
802024
A learning-based spectrum access Stackelberg game: Friendly jammer-assisted communication confrontation
N Qi, W Wang, M Xiao, L Jia, S Jin, Q Zhu, TA Tsiftsis
IEEE Transactions on Vehicular Technology 70 (1), 700-713, 2021
712021
Channel modeling and performance analysis for UAV relay systems
X Chen, X Hu, Q Zhu, W Zhong, B Chen
China Communications 15 (12), 89-97, 2018
622018
Path loss and shadowing for UAV-to-ground UWB channels incorporating the effects of built-up areas and airframe
H Ni, Q Zhu, B Hua, K Mao, Y Pan, F Ali, W Zhong, X Chen
IEEE Transactions on Intelligent Transportation Systems, 2024
612024
3D non‐stationary geometry‐based multi‐input multi‐output channel model for UAV‐ground communication systems
Q Zhu, Y Wang, K Jiang, X Chen, W Zhong, N Ahmed
IET Microwaves, Antennas & Propagation 13 (8), 1104-1112, 2019
612019
RIS-UAV enabled worst-case downlink secrecy rate maximization for mobile vehicles
X Liu, Y Yu, B Peng, XB Zhai, Q Zhu, VCM Leung
IEEE Transactions on Vehicular Technology 72 (5), 6129-6141, 2022
582022
MmWave beamforming for UAV communications with unstable beam pointing
W Zhong, L Xu, Q Zhu, X Chen, J Zhou
China communications 16 (1), 37-46, 2019
572019
Geometry-based stochastic line-of-sight probability model for A2G channels under urban scenarios
Q Zhu, F Bai, M Pang, J Li, W Zhong, X Chen, K Mao
IEEE Transactions on Antennas and Propagation 70 (7), 5784-5794, 2022
552022
Space-based electromagnetic spectrum sensing and situation awareness
Y Huang, H Cui, Y Hou, C Hao, W Wang, Q Zhu, J Li, Q Wu, J Wang
Space: Science & Technology 4, 0109, 2024
542024
Map-based channel modeling and generation for U2V mmWave communication
Q Zhu, K Mao, M Song, X Chen, B Hua, W Zhong, X Ye
IEEE Transactions on Vehicular Technology 71 (8), 8004-8015, 2022
542022
Highly efficient rejection method for generating Nakagami-m sequences
QM Zhu, XY Dang, DZ Xu, XM Chen
Electronics letters 47 (19), 1100-1101, 2011
542011
Channel estimation enhancement with generative adversarial networks
T Hu, Y Huang, Q Zhu, Q Wu
IEEE transactions on cognitive communications and networking 7 (1), 145-156, 2020
502020
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