A geometry-based non-stationary MIMO channel model for vehicular communications

This paper derives a non-stationary multiple-input multiple-output(MIMO) from the one-ring scattering model. The proposed channel model characterizes vehicular radio propagation channels with considerations of moving base and mobile stations, which makes the angle of arrivals (AOAs) along with the angle of departures (AODs) time-variant. We introduce the methodology of including the time-variant impacts when characterizing non-stationary radio propagation channels through the geometrical channel modelling approach. We analyze the statistical properties of the proposed channel model including the local time-variant autocorrelation function (ACF) and the space cross-correlation functions (CCFs). We show that the model developed in this paper for non-stationary scenarios includes the existing one-ring wide-sense stationary channel model as its special case.

[1]  Xiang Cheng,et al.  Wideband Channel Modeling and Intercarrier Interference Cancellation for Vehicle-to-Vehicle Communication Systems , 2013, IEEE Journal on Selected Areas in Communications.

[2]  Daniel U. Campos-Delgado,et al.  Geometry-Based Statistical Modeling of Non-Stationary MIMO Vehicle-to-Vehicle Channels , 2015, DIVANet@MSWiM.

[3]  David W. Matolak,et al.  Worse-than-Rayleigh fading: Experimental results and theoretical models , 2011, IEEE Communications Magazine.

[4]  Xiang Cheng,et al.  Channel Prediction Based Scheduling for Data Dissemination in VANETs , 2017, IEEE Communications Letters.

[5]  Jiajing Chen,et al.  Measurement-Based Massive MIMO Channel Modeling for Outdoor LoS and NLoS Environments , 2017, IEEE Access.

[6]  Daniel U. Campos-Delgado,et al.  Modeling of Non-Stationary Double-Rayleigh Fading Channels for Mobile-to-Mobile Communications , 2016 .

[7]  Matthias Pätzold,et al.  Capacity studies of MIMO channel models based on the geometrical one-ring scattering model , 2004, 2004 IEEE 15th International Symposium on Personal, Indoor and Mobile Radio Communications (IEEE Cat. No.04TH8754).

[8]  Subir Biswas,et al.  Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety , 2006, IEEE Communications Magazine.

[9]  Xiang Cheng,et al.  5G-Enabled Cooperative Intelligent Vehicular (5GenCIV) Framework: When Benz Meets Marconi , 2017, IEEE Intelligent Systems.

[10]  Matthias Pätzold,et al.  A non-stationary one-ring scattering model , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[11]  Xiang Cheng,et al.  An adaptive geometry-based stochastic model for non-isotropic MIMO mobile-to-mobile channels , 2009, IEEE Transactions on Wireless Communications.

[12]  Gerd Ascheid,et al.  Analysis of the Local Quasi-Stationarity of Measured Dual-Polarized MIMO Channels , 2015, IEEE Transactions on Vehicular Technology.

[13]  B. Ai,et al.  Characterization of Quasi-Stationarity Regions for Vehicle-to-Vehicle Radio Channels , 2015, IEEE Transactions on Antennas and Propagation.

[14]  Matthias Patzold,et al.  A space-time channel simulator for MIMO channels based on the geometrical one-ring scattering model , 2004 .

[15]  Xiang Cheng,et al.  D2D for Intelligent Transportation Systems: A Feasibility Study , 2015, IEEE Transactions on Intelligent Transportation Systems.

[16]  Matthias Pätzold,et al.  Modeling, analysis, and simulation of MIMO mobile-to-mobile fading channels , 2008, IEEE Transactions on Wireless Communications.

[17]  Byeong-Woo Kim,et al.  Usability Analysis of Collision Avoidance System in Vehicle-to-Vehicle Communication Environment , 2014, J. Appl. Math..