85 citations · 197 across the 12 of their papers we have counts for
12 papers · 1 filter
Sparse Bayesian Learning-Based 3D Spectrum Environment Map Construction-Sampling Optimization, Scenario-Dependent Dictionary Construction and Sparse Recovery
Jie Wang, Qiuming Zhu, Zhipeng Lin +5
The spectrum environment map (SEM), which can visualize the information of invisible electromagnetic spectrum, is vital for monitoring, management, and security of spectrum resourc…
Channel Modeling for UAV-to-Ground Communications with Posture Variation and Fuselage Scattering Effect
Boyu Hua, Haoran Ni, Qiuming Zhu +5
Unmanned aerial vehicle (UAV)-to-ground (U2G) channel models play a pivotal role for reliable communications between UAV and ground terminal. This paper proposes a three-dimensiona…
A Realistic 3D Non-Stationary Channel Model for UAV-to-Vehicle Communications Incorporating Fuselage Posture
Boyu Hua, Tongtong Zhou, Qiuming Zhu +4
Considering the unmanned aerial vehicle (UAV) three-dimensional (3D) posture, a novel 3D non-stationary geometry-based stochastic model (GBSM) is proposed for multiple-input multip…
Geometry-Based Stochastic Probability Models for the LoS and NLoS Paths of A2G Channels under Urban Scenario
Minghui Pang, Qiuming Zhu, Cheng-Xiang Wang +4
Path probability prediction is essential to describe the dynamic birth and death of propagation paths, and build the accurate channel model for air-to-ground (A2G) communications.…
Height-Dependent LoS Probability Model for A2G MmWave Communications under Built-up Scenarios
Minghui Pang, Qiuming Zhu, Fei Bai +4
Based on the three-dimensional propagation characteristic under built-up scenarios, a height-dependent line-of-sight (LoS) probability model for air-to-ground (A2G) millimeter wave…
Geometry-Based Stochastic Line-of-Sight Probability Model for A2G Channels under Urban Scenarios
Qiuming Zhu, Fei Bai, Minghui Pang +4
Line-of-sight (LoS) path is essential for the reliability of air-to-ground (A2G) communications, but the existence of LoS path is difficult to predict due to random obstacles on th…
Machine Learning-Based 3D Channel Modeling for U2V mmWave Communications
Kai Mao, Qiuming Zhu, Maozhong Song +4
Unmanned aerial vehicle (UAV) millimeter wave (mmWave) technologies can provide flexible link and high data rate for future communication networks. By considering the new features…
Map-based Channel Modeling and Generation for U2V mmWave Communication
Qiuming Zhu, Kai Mao, Maozhong Song +4
Unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) technologies have a promising prospect in the future communication networks. By considering the factors of three-dimens…
A 3D Non-Stationary GBSM for Vehicular Visible Light Communication MISO Channels
A. Al-Kinani, C. -X. Wang, Q. Zhu +3
The potential of using visible light communication (VLC) technologies for vehicular communication networks has recently attracted much attention. The underlying VLC channels, as a…
Effects of Digital Map on the RT-based Channel Model for UAV mmWave Communications
Qiuming Zhu, Shan Jiang, Cheng-Xiang Wang +4
Based on the geometry and ray tracing (RT) theory, a millimeter wave (mmWave) channel model and parameter computation method for unmanned aerial vehicle (UAV) assisted air-to-groun…
A Non-Stationary VVLC MIMO Channel Model for Street Corner Scenarios
Qingshan Chen, Cheng-Xiang Wang, Jian Sun +2
In recent years, the application potential of visible light communication (VLC) technology as an alternative and supplement to radio frequency (RF) technology has attracted people'…
A Practical Non-Stationary Channel Model for Vehicle-to-Vehicle MIMO Communications
Weidong Li, Qiuming Zhu, Cheng-Xiang Wang +3
In this paper, a practical model for non-stationary Vehicle-to-Vehicle (V2V) multiple-input multiple-output (MIMO) channels is proposed. The new model considers more accurate outpu…