A General 3D Non-Stationary Twin-Cluster Model for Vehicle-to-Vehicle MIMO Channels

Yang, Ying; Zhu, Qiuming; Li, Weidong; Chen, Xiaomin; Zhong, Weizhi; Yu, Xiangbin; Masuda, Kai

doi:10.1109/wcsp.2018.8555598

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Finally, by substituting (33)- (35) into (22), the final result of SCF in our proposed model can be obtained. Due to time-variant communication environments, SCF is also time-dependent.…”

Section: Time-variant Scfsmentioning

confidence: 99%

“…Very recently, a general 3D nonstationary GBSM between base station and MT with 3D arbitrary trajectories and 3D antenna arrays was proposed in [34]. is idea was adopted by [35] to model the 3D V2V channels allowing MTand MR with 3D arbitrary trajectories. However, the details of channel parameter computation and theoretical analyses of SCF, TCF, and DPSD were lacked.…”

Section: Introductionmentioning

confidence: 99%

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A General 3D Nonstationary Vehicle-to-Vehicle Channel Model Allowing 3D Arbitrary Trajectory and 3D-Shaped Antenna Array

Zhu

Yang

et al. 2019

International Journal of Antennas and Propagation

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Most of the existing channel model for multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communications only considered that the terminals were equipped with linear antenna arrays and moved with fixed velocities. Nevertheless, under the realistic environment, those models are not practical since the velocities and trajectories of mobile transmitter (MT) and mobile receiver (MR) could be time-variant and unpredictable due to the complex traffic conditions. This paper develops a general 3D nonstationary V2V channel model, which is based on the traditional geometry-based stochastic models (GBSMs) and the twin-cluster approach. In contrast to the traditional models, this new model is characterized by 3D scattering environments, 3D antenna arrays, and 3D arbitrary trajectories of both terminals and scatterers. The calculating methods of channel parameters are also provided. In addition, the statistical properties, i.e., spatial-temporal correlation function (STCF) and Doppler power spectrum density (DPSD), are derived in detail. Simulation results have demonstrated that the output statistical properties of the proposed model agree well with the theoretical and measured results, which verifies the effectiveness of theoretical derivations and channel model as well.

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“…Finally, by substituting (33)- (35) into (22), the final result of SCF in our proposed model can be obtained. Due to time-variant communication environments, SCF is also time-dependent.…”

Section: Time-variant Scfsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A General 3D Nonstationary Vehicle-to-Vehicle Channel Model Allowing 3D Arbitrary Trajectory and 3D-Shaped Antenna Array

Zhu

Yang

et al. 2019

International Journal of Antennas and Propagation

Self Cite

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“…The continuously arbitrary vehicular movement trajectory and soft cluster power handover are modeled. The generality of the proposed model is validated by comparing with measurements as well as ray-tracing (RT)-based results [30]. Substantially, in order to capture the non-stationarity, evolution algorithms are extensively used for IS GBSMs.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the direction of movement is assumed constant [26]- [29], and thus, it can only characterize channel properties with linear trajectories. Although the curved trajectory is described [30], array evolution is neglected and the derivation of time correlation with time-variation of angles is not fully demonstrated.…”

Section: Introductionmentioning

confidence: 99%

A novel 3D non-stationary vehiele-to-vehiele channel model with circular arc motions

Su,

Chen,

Yang

2024

IEICE Trans. Commun.

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In this paper, a cluster-based three-dimensional (3D) nonstationary vehicle-to-vehicle (V2V) channel model with circular arc motions and antenna rotates is proposed. The channel model simulates the complex urban communication scenario where clusters move with arbitrary velocities and directions. A novel cluster evolution algorithm with time-array consistency is developed to capture the non-stationarity. For time evolution, the birth-and-death (BD) property of clusters including birth, death, and rebirth are taken into account. Additionally, a visibility region (VR) method is proposed for array evolution, which is verified to be applicable to circular motions. Based on the Taylor expansion formula, a detailed derivation of space-time correlation function (ST-CF) with circular arc motions is shown. Statistical properties including ST-CF, Doppler power spectrum density (PSD), quasi-stationary interval, instantaneous Doppler frequency, root mean square delay spread (RMS-DS), delay PSD, and angular PSD are derived and analyzed. According to the simulated results, the nonstationarity in time, space, delay, and angular domains is captured. The presented results show that motion modes including linear motions as well as circular motions, the dynamic property of the scattering environment, and the velocity of the vehicle all have significant impacts on the statistical properties.

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3D MIMOAntenna Designs

Sharawi

2020

Wiley 5G Ref

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Multiple‐input multiple‐output (MIMO) technology has been a key driver in the development of fourth‐generation wireless systems and will continue to be utilized in the upcoming fifth‐generation one. MIMO was an excellent technology to make use of multipath effects and enhance the system capacity dramatically. A new technology that is based on MIMO that utilizes large amounts of antennas at the base‐station side to simultaneously send dedicated beams and create dedicated channels for various users has been identified and will be deployed with fifth‐generation systems to enhance the channel capacity even more. This technology is called massive‐MIMO (MaMI). The majority of works that addressed MaMI focused on one dimensional (azimuthal) beam steering. Adding the second dimension (elevation) to the original MaMI systems has been denoted as three‐dimensional MIMO (3D‐MIMO) since the beams will cover the 3D space in front of the MaMI array, thus enhancing coverage, reducing interference and enhancing capacity. This article focuses on 3D‐MIMO antenna array systems, their performance metrics and some examples of actual implementations at microwave and mm‐wave bands.

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A General 3D Non-Stationary Twin-Cluster Model for Vehicle-to-Vehicle MIMO Channels

Cited by 5 publications

References 18 publications

A General 3D Nonstationary Vehicle-to-Vehicle Channel Model Allowing 3D Arbitrary Trajectory and 3D-Shaped Antenna Array

A General 3D Nonstationary Vehicle-to-Vehicle Channel Model Allowing 3D Arbitrary Trajectory and 3D-Shaped Antenna Array

A novel 3D non-stationary vehiele-to-vehiele channel model with circular arc motions

3D MIMOAntenna Designs

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