A Novel Segment-Based Model for Non-Stationary Vehicle-to-Vehicle Channels With Velocity Variations

Abstract

By considering the velocity variations of both terminals and moving scatterers, a general segment-based model for non-stationary vehicle-to-vehicle (V2V) channels is proposed in this paper. The time evolving channel parameters, i.e., Doppler frequencies, angles of arrival and departure, path delays, and path powers, are analyzed and simplified by the Taylor series expansions. The proposed model can be applied for realistic V2V communication environments and explicitly reveal the impact of velocity variations on the channels. In addition, the theoretical statistical properties, i.e., the temporal correlation function (TCF), Doppler power spectrum density (DPSD), level-crossing rate (LCR), and average fading duration (AFD) are also analyzed and derived. Simulation results under four typical V2V scenarios show that the theoretical results agree well with the simulated and measured ones, which verifies the effectiveness of both the proposed model and the derivations. INDEX TERMSVehicle-to-vehicle (V2V) channel, non-stationary channel model, velocity variation, statistical property. DAZHUAN XU received the B.S. degree from the Nanjing Institute of Technology, Nanjing, China, in 1983, and the M.S. and Ph.D. degrees in communication and information systems from the Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, in 1986 and 2001, respectively. He has been with the College of Electronic and Information Engineering, NUAA, where he is currently a Full Professor. His research interests include digital communications, software radio, and coding theory. FEI BAI received the B.S. degree in information engineering from the Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2019, where she is currently pursuing the M.S. degree in electronics and communication engineering. Her research interests include the MIMO channel models and channel measurements.

A Novel GBSM for Non-Stationary V2V Channels Allowing 3D Velocity Variations

“…In this paper, we considered the 3D velocity variation for different time instants, while the model in [31] merely considered 2D velocity variations. Thus, the DPSDs of the proposed model were more precise than the model in [31] compared to the theoretical results. In addition, the velocity parameters v Tx , v Rx and the acceleration parameters a Tx , a Rx affected the Doppler frequency, which showed the perfect comprehension among the theoretical and simulated consequences over time.…”

“…The theoretical and simulated ACFs at three different moments were derived and shown in Figure 4 . By comparing the ACFs of this model and the reference model in [ 31 ] at various time instants, it was obvious that the velocity parameters had a significant impact on the ACFs. Due to the fact that the model in [ 31 ] only considered 2D velocity variations, the proposed model provided better simulated outcomes with respect to the theoretical outcomes when the velocity changed arbitrarily.…”

“…Therefore, an updated 3D channel model was addressed in [ 27 ] with accurate Doppler frequency. By taking notice of the fact that the majority of the mentioned models took only the fixed velocity of the vehicle into account, in realistic traffic environments, the velocity could be time-variant, whereas the time-variant velocities were taken into account in [ 28 , 29 , 30 , 31 ], where the trajectories were 2D and also 1D for simplicity. Very recently, a non-stationary GBSM among the terminal and vehicle with 3D arbitrary trajectories and 3D antenna arrays with the consideration of fixed velocity was presented in [ 32 ].…”

“…The concept of this paper was obtained from [ 31 , 32 ] to model the V2V channels allowing 3D trajectories, but the proposed model only supported 3D constant velocity. The goal of this paper was to address this void.…”

Wireless fading channels performance based on Taylor expansion and compressed sensing: A comparative approach

“…Extending to 5G applications of Taylor expansion, Li et al 9 Taylor expand the non‐analytic distribution proposing a nonlinear equalization scheme, while Lv et al 10 consider the Taylor expansion throughput in a device‐to‐device interference environment. Furthermore, a nonstationary channel model accounting for Doppler frequency estimation 11 is utilized by Taylor expansion of second degree, as is the case of our paper, to model channel parameters.…”