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In this paper, an extension spatial channel model (SCM) for vehicle-to-vehicle (V2V) communications is proposed. To efficiently illustrate the real-world scenarios and reflect nonstationary properties of V2V channels, all effective scattering objects are subdivided into three categories of clusters according to the relative position of clusters. Besides, a birth-death process is introduced to model the appearance and disappearance of clusters on both the array and time axes. Their impacts on V2V channels are investigated via statistical properties including correlation functions. Additionally, a closed-form expression of channel impulse response (CIR) is derived from an extension SCM and cluster-based models. Furthermore, the spatial and frequency statistical properties of the reference model are thoroughly investigated. Finally, simulation results show that the proposed SCM V2V model is in close agreement with previously reported results, thereby validating the accuracy and effectiveness of the proposed model.

In recent years, research into vehicle-to-vehicle (V2V) communications has gained strong momentum due to its potential in facilitating the implementation of Internet of Vehicles (IoV) and Intelligent Transportation Systems (ITS) [

It is well known that the set and deployment of the IEEE 802.11p standard and V2V wireless system require a solid understanding of the V2V radio propagation channel and corresponding mathematical channel characterization knowledge. This understanding can also contribute to the design and incremental improvement of effective signal processing techniques [

The different approaches to model V2V models can be roughly split into three categories: deterministic models, stochastic models, and geometry-based stochastic models (GBSMs) [

Even though many V2V channel models have been proposed over the past decade, there are still pressing needs to model V2V channels considering both the effect of randomly distributed scatterers and nonstationary property. In this regard, we extend the work described in [

An extended cluster-based SCM for V2V communications is proposed. All effective scattering objects are subdivided into three categories of clusters according to the position of clusters with respect to vehicles (Tx/Rx). Three different locations between the Tx and Rx have been distinguished, which represents a particular type of physical situation, i.e., vehicles are approaching, passing, and leaving clusters. This paper focuses on the effect of locations of scatterers and nonstationary channel characterizations.

To statistically model the nonstationary V2V channels, the reference model incorporates the dynamic variations of multipath components, which includes delay and angular properties as well as dynamic evolution of clusters as the Tx/Rx move. The proposed SCM V2V channel model could be useful for getting a more in-depth understanding of V2V nonstationary channel behavior.

Statistical properties of the reference model are derived and investigated, including time-variant transfer function (TVTF), temporal autocorrelation function (ACF), Doppler power spectral density (PSD), and space-time-frequency correlation function (STFCF). Simulation results demonstrate the validity and effectiveness of the proposed model.

The rest of the paper is organized as follows. Section

In practical V2V scattering environments as shown in Figure

Geometry-based stochastic V2V channel model: (a) a typical V2V scattering scene; (b) two-dimensional V2V channel model.

Three categories of clusters with respect to Tx/Rx. (a) Ahead cluster. (b) Between cluster. (c) Behind cluster.

Figure

Figure

Figure

We consider the street scattering environment in microcell urban as depicted in Figure

Under NLoS conditions in the absence of LoS components, each realization consists of

The key parameters of the proposed model are summarized in Table

Definition of the parameters in the V2V model.

Symbol | Definition |
---|---|

Power of the | |

Number of “ahead,” “between,” and “behind” clusters, respectively | |

Total number of clusters ( | |

Number of subpaths per cluster | |

Antenna gains of Tx and Rx, respectively | |

Number of antennas at Tx and Rx, respectively | |

AoD of the | |

AoA of the | |

Angle of Rx velocity vector | |

Relative speed of Rx velocity vector | |

Distance between clusters and Tx/Rx antenna elements, respectively | |

Antenna elements spacing at Tx and Rx, respectively | |

Phase of the | |

Wave number, | |

Square root of |

In (

Under LoS conditions, the CIR of SCM V2V model can be represented by (

Motivated by the mentioned approach in [

Let us consider the proposed channel model with multiple clusters in “ahead,” “between,” and “behind” three regions to describe different taps of V2V channels. There exist

To describe the cluster evolution on the time axis, we define the time-dependent channel fluctuations

The number of newly generated clusters at time instant

The process of the newly generated cluster observed at both Tx and Rx antennas can be summarized in Table

The process of newly generated clusters.

Step | Description |
---|---|

1 | Generate initial indices |

2 | Evolve the cluster at the Tx antenna from |

3 | Evolve the cluster at the Rx antenna from |

4 | Update the cluster sets observed at both the Tx and the Rx antennas |

The time-variant transfer function (TVTF)

To illustrate the effect of clusters on the temporal autocorrelation function (ACF) of the proposed model, the expression of ACF

The Doppler power spectral density (PSD)

It is noteworthy that the Doppler PSD is time

The normalized space-time-frequency correlation function (STFCF) between time-variant transfer functions

For the sake of simplicity, we assume that the relative delays and Rician factor are constants at time instant

In the simulations, the proposed extended SCM V2V channel model has been implemented in the common environment (Table

“Ahead cluster” angles:

“Between cluster” angles:

“Behind cluster” angles:

The standard deviations are less than one degree. Considering the angles of subpaths in a cluster within the differential angle

Figure

ACF for three categories of clusters in different regions (note: the average velocities of moving scatterers

Behavior of PSD presented in Figure

Figure

The absolute value of STFCF for clusters in different regions. (a) STFCF for ahead clusters. (b) STFCF for between clusters. (c) STFCF for behind clusters.

This paper explores an extension SCM V2V channel model. We describe the channel characteristics of both LoS and single-bounced clusters. Furthermore, this paper further analyzes the dynamics of clusters by introducing a birth-death process. Based on this model, we have derived the mathematical expressions of channel characteristics. By assuming an isotropic single-bounced scattering scenario, simulation results show the relationships between correlation functions and the locations of different clusters. We have pointed out the calculation methods of coherent time for V2V channels in different scattering scenarios.

The data used to support the findings of this study are available from the corresponding author upon request.

The authors declare that they have no conflicts of interest.

This work was supported by the National Natural Science Foundation of China under Grant no. 61673253, the Chinese Postdoctoral Science Foundation under Grant no. 2020M683562, the Specialized Research Fund for Xi’an University Talent Service Enterprise Project under Grant no. GXYD7.11, the Special Scientific Research Project of Shaanxi Provincial Department of Education under Grant no. 20JK0645, and the Specialized Research Fund for Shaoxing Keqiao West-Tex Textile Industry Innovative Institute Project under Grant no. 19KQYB11.