A 3-D Non-Stationary Wideband Geometry-Based Channel Model for MIMO Vehicle-to-Vehicle Communications in Tunnel Environments

Jiang, Hao; Zhang, Zaichen; Wu, Liang; Dang, Jian; Gui, Guan

doi:10.1109/tvt.2019.2918333

Cited by 90 publications

(57 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the literature, several works have been proposed for channel modeling in different applications. In a specific scenario, e.g., the works of [18], [19] propose different channel models for vehicular-to-vehicular communications in 5G networks. Nevertheless, for more general scenarios such as indoor/outdoor in a urban/rural environment, there are many channel models proposed based on measurement campaigns such as 3GPP [12], International Mobile Telecommunications (IMT)-2020 [14], Quasi Deterministic Radio channel Generator (QuaDRiGa) [16], Millimetre-Wave Based Mobile Radio Access Network for Fifth Generation Integrated Communications (mmMAGIC) [20], Mobile and wireless communications Enablers for the Twenty-twenty Information Society (METIS) 2020 [21].…”

Section: Literature Reviewmentioning

confidence: 99%

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

et al. 2020

View full text Add to dashboard Cite

In the fifth-generation (5G) mobile networks, it is expected that users experience high throughputs with an ultra-low-latency network, while a massive number of devices are connected to the network. However, in remote rural areas, there is still a large number of people that do not have access to broadband Internet. To overcome this issue, a possible strategy is to exploit the excellent propagation conditions of very high frequency (VHF) and ultra-high frequency (UHF) bands by allowing secondary spectrum reuse in the TV white space (TVWS) channels. But for that, a reliable channel model is required to perform valid coverage and data rate prediction studies. In this paper, a channel model is proposed that takes into account large and small scale fading effects, as well as the particularities of such remote rural areas. The proposed model makes use of measurements along with the clustered delay line (CDL) profiles from 3rd Generation Partnership Project (3GPP). It is a simple model to implement and can be used to provide fast link and system-level simulations. Numerical and analytical results are provided to validate the proposed model and a data rate evaluation is carried out for single-input single-output (SISO) and multiple-input multiple-output (MIMO) configurations, as well as for single-polarized (SP) and dual-polarized (DP) antennas. INDEX TERMS Channel modeling, remote rural areas, CDL, MIMO and dual-polarized antennas.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

et al. 2020

View full text Add to dashboard Cite

show abstract

“…In addition, DL has been applied in multiple-input and multiple-output (MIMO) [17], non-orthogonal multiple-access (NOMA), and cognitive radio (CR). For example, H. Huang, et al [25], [26] proposed a fast beam forming technology for downlink MIMO based on unsupervised learning.…”

Section: Introductionmentioning

confidence: 99%

Generalized Automatic Modulation Classification Under Non-Gaussian Noise with Varying SNR Conditions: A CNN Enable Method

Wang¹,

Gui²,

Ohtsuki³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Automatic modulation classification (AMC) is an critical step to identify signal modulation types so as to enable more accurate demodulation in the non-cooperative scenarios. Convolutional neural network (CNN)-based AMC is believed as one of the most promising methods with great classification accuracy. However, the conventional CNN-based methods are lack of generality capabilities under time-varying signal-to-noise ratio (SNR) conditions, because these methods are merely trained on specific datasets and can only work at the corresponding condition. In this paper, a novel CNN-based generalized AMC method is proposed, and a more realistic scenario is considered, including white non-Gaussian noise and synchronization error. Its generalization capability stems from the mixed datasets under varying noise scenarios, and the CNN can extract common features from these datasets. Simulation results show that our proposed architecture can achieve higher robustness and generalization than the conventional ones.

show abstract

“…e nonstationary scenarios of MIMO technologies for high-speed train and Metro communications have drawn attention. Up to present, there are two main cases of nonstationary scenarios: one is the movement of transmitter or receiver and the other is the movement of transmitter and receiver [1][2][3][4][5][6][7][8][9][10][11][12]. e channel modeling can be based on two-dimensional (2D) [1][2][3][4][5] and three-dimensional (3D) [6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Up to present, there are two main cases of nonstationary scenarios: one is the movement of transmitter or receiver and the other is the movement of transmitter and receiver [1][2][3][4][5][6][7][8][9][10][11][12]. e channel modeling can be based on two-dimensional (2D) [1][2][3][4][5] and three-dimensional (3D) [6][7][8][9][10][11][12]. According to the 3GPP (3GPP TR 25.996) spatial channel model (SCM) [1][2][3][4][5][6] and WINNER II channel model [7][8][9][10][11][12], the geometry-based single-bounce (GBSB) [1][2][3][4][5] and geometry-based stochastic model (GBSM) [6][7][8][9][10][11][12] are used to describe MIMO propagation channels.…”

Section: Introductionmentioning

confidence: 99%

“…e nonstationary scenarios investigated include the high altitude unmanned aerial vehicles (UAV) MIMO air-to-ground communications [7,8], the vehicle-tovehicle communications in tunnel [9,10] and other scattering environments [11,12], the base-station-to-vehicle communications in tunnel [5] and other scattering environments [1,2], and so on. In these scenarios, the influences of different moving velocities, moving times, moving directions, and moving trajectories on spatial cross-correlation and autocorrelation are analyzed [6][7][8][9][10][11][12]. In [1,2], the authors have researched the multielement antennas systems in mobile fading channels and have considered that the local scatterers were only around the mobile user (MS) in 2 × 2 MIMO channel, the base station (BS) is fixed, the BS and the MS are both two-element antennas array, and they also derived a space-time correlation for MIMO systems in mobile fading channels.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Space-Time Correlation for Three-Dimensional MIMO Channel Model Using Leaky Coaxial Cables in Rectangular Tunnel

Zhang

Zheng

2020

International Journal of Antennas and Propagation

View full text Add to dashboard Cite

The rapid development of high-speed train and Metro communications has provided new challenges for the application of MIMO technologies. Therefore, we propose a three-dimensional (3D) multiple-input multiple-output (MIMO) channel model using leaky coaxial cable (LCX) in a rectangular tunnel. The channel model is based on geometry-based single-bounce (GBSB) channel model and the electric field distribution of LCX in the tunnel environment. The theoretical expressions of channel impulse response (CIR) and space-time correlation function (CF) are also derived and analyzed. The CFs for different model parameters (moving velocity and moving time) and different regions of the tunnel are simulated by Monte Carlo method to verify the theoretical derivation at 1.8 GHz. In the same parametric configuration of nonstationary tunnel scenarios, the time delay of the first minimum value of CFs for LCX-MIMO is 1/5 of the time delay of the minimum value of CFs for dipole antennas MIMO when the train moving velocity is 360 km/h. It is shown that, for MIMO system, the performance of using LCXs is better than using dipole antennas.

show abstract

A 3-D Non-Stationary Wideband Geometry-Based Channel Model for MIMO Vehicle-to-Vehicle Communications in Tunnel Environments

Cited by 90 publications

References 41 publications

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

A CDL-Based Channel Model With Dual-Polarized Antennas for 5G MIMO Systems in Rural Remote Areas

Generalized Automatic Modulation Classification Under Non-Gaussian Noise with Varying SNR Conditions: A CNN Enable Method

Space-Time Correlation for Three-Dimensional MIMO Channel Model Using Leaky Coaxial Cables in Rectangular Tunnel

Contact Info

Product

Resources

About