A novel 3D non-stationary UAV-MIMO channel model and its statistical properties

The wireless communication systems based on Unmanned Aerial Vehicles (UAVs) have found a wide range of applications recently. In this paper, we propose a new three-dimensional (3D) non-stationary multiple-input multiple-output (MIMO) channel model for the communication links between the UAV and mobile terminal (MT). The new model originates the traditional geometry-based stochastic models (GBSMs) but considers the non-stationary propagation environment due to the rapid movements of the UAV, MT, and clusters. Meanwhile, the upgrade time evolving algorithms of time-variant channel parameters, i.e., the path number based on birth-death processes of clusters, path delays, path powers, and angles of arrival and departure, are developed and optimized. In addition, the statistical properties of proposed GBSM including autocorrelation function (ACF), cross-correlation function (CCF), and Doppler power spectrum density (DPSD) are investigated and analyzed. Simulation results demonstrate that our proposed model provides a good agreement on the statistical properties with the corresponding derived theoretical ones, which indicates its usefulness for the performance evaluation and validation of the UAV based communication systems.

[1]  Chen He,et al.  A novel multiuser HAP-MIMO channel model based on birth-death process , 2016, 2016 IEEE International Conference on Communications (ICC).

[2]  Lianfen Huang,et al.  Ray Tracing Based Wireless Channel Modeling over the Sea Surface near Diaoyu Islands , 2015, 2015 First International Conference on Computational Intelligence Theory, Systems and Applications (CCITSA).

[3]  Robert W. Stewart,et al.  The Fisher–Bingham Spatial Correlation Model for Multielement Antenna Systems , 2009, IEEE Transactions on Vehicular Technology.

[4]  Xiaofei Zhang,et al.  Direction of Departure (DOD) and Direction of Arrival (DOA) Estimation in MIMO Radar with Reduced-Dimension MUSIC , 2010, IEEE Communications Letters.

[5]  Lu Bai,et al.  Recent advances and future challenges for massive MIMO channel measurements and models , 2016, Science China Information Sciences.

[6]  Chen He,et al.  A 3-D Wideband Model Based on Dynamic Evolution of Scatterers for HAP-MIMO Channel , 2017, IEEE Communications Letters.

[7]  Xiaohu You,et al.  A General 3-D Non-Stationary 5G Wireless Channel Model , 2018, IEEE Transactions on Communications.

[8]  Fabio Dovis,et al.  Small-scale fading for high-altitude platform (HAP) propagation channels , 2002, IEEE J. Sel. Areas Commun..

[9]  Caijun Zhong,et al.  Wireless Information and Power Transfer With Full Duplex Relaying , 2014, IEEE Transactions on Communications.

[10]  Bo,et al.  Stationarity Intervals of Time-Variant Channel in High Speed Railway Scenario , 2012 .

[11]  Ping Zhang,et al.  An effective approach to 5G: Wireless network virtualization , 2015, IEEE Communications Magazine.

[12]  Cheng-Xiang Wang,et al.  A Non-Stationary 3-D Wideband Twin-Cluster Model for 5G Massive MIMO Channels , 2014, IEEE Journal on Selected Areas in Communications.

[13]  Athanasios G. Kanatas,et al.  Wideband HAP-MIMO Channels: A 3-D Modeling and Simulation Approach , 2014, Wirel. Pers. Commun..

[14]  Xiang Cheng,et al.  A 3D Geometry-Based Stochastic Channel Model for UAV-MIMO Channels , 2017, 2017 IEEE Wireless Communications and Networking Conference (WCNC).

[15]  Milica Stojanovic,et al.  A MIMO Radio Channel Model for Low-Altitude Air-to-Ground Communication Systems , 2015, 2015 IEEE 82nd Vehicular Technology Conference (VTC2015-Fall).

[16]  Qihui Wu,et al.  Cognitive Internet of Things: A New Paradigm Beyond Connection , 2014, IEEE Internet of Things Journal.

[17]  Qing Guo,et al.  Statistical modeling of the high altitude platform dual-polarized MIMO propagation channel , 2017, China Communications.

[18]  Rui Zhang,et al.  Wireless communications with unmanned aerial vehicles: opportunities and challenges , 2016, IEEE Communications Magazine.

[19]  David W. Matolak,et al.  Air–Ground Channel Characterization for Unmanned Aircraft Systems Part II: Hilly and Mountainous Settings , 2017, IEEE Transactions on Vehicular Technology.

[20]  Pavel Pechac,et al.  The UAV Low Elevation Propagation Channel in Urban Areas: Statistical Analysis and Time-Series Generator , 2013, IEEE Transactions on Antennas and Propagation.

[21]  Alagan Anpalagan,et al.  Opportunistic Spectrum Access in Unknown Dynamic Environment: A Game-Theoretic Stochastic Learning Solution , 2012, IEEE Transactions on Wireless Communications.

[22]  Mohsen Guizani,et al.  A Cooperation Strategy Based on Nash Bargaining Solution in Cooperative Relay Networks , 2008, IEEE Transactions on Vehicular Technology.

[23]  Cheng-Xiang Wang,et al.  A Novel 3D Non-Stationary Wireless MIMO Channel Simulator and Hardware Emulator , 2018, IEEE Transactions on Communications.

[24]  Xiang Cheng,et al.  Propagation Channel Characterization, Parameter Estimation, and Modeling for Wireless Communications , 2016 .

[25]  Yan Chen,et al.  On cognitive radio networks with opportunistic power control strategies in fading channels , 2008, IEEE Transactions on Wireless Communications.

[26]  Athanasios G. Kanatas,et al.  Three-Dimensional HAP-MIMO Channels: Modeling and Analysis of Space-Time Correlation , 2010, IEEE Transactions on Vehicular Technology.

[27]  Qihui Wu,et al.  Spatial-Temporal Opportunity Detection for Spectrum-Heterogeneous Cognitive Radio Networks: Two-Dimensional Sensing , 2013, IEEE Transactions on Wireless Communications.

[28]  Caijun Zhong,et al.  Wireless Information and Power Transfer in Relay Systems With Multiple Antennas and Interference , 2015, IEEE Transactions on Communications.

[29]  Lianfen Huang,et al.  Modeling of wireless channel between UAV and vessel using the FDTD method , 2014 .