V2V Channel Research Articles

STAR-RIS-NOMA empowered vehicle-to-vehicle communications: Outage and ergodic capacity analysis

This paper delves into the performance evaluation of a non-orthogonal multiple access (NOMA) enabled vehicle-to-vehicle (V2V) communication system empowered by simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS). Herein, we consider that a moving access point (AP) transmits superimposed signals to nearby and distant NOMA vehicles simultaneously via reflection and transmission through a STAR-RIS equipped vehicle with 2N reconfigurable elements, respectively. Specifically, by characterizing all V2V channels as double-Rayleigh fading distributed, we derive the outage probability (OP) and ergodic capacity (EC) expressions for each NOMA vehicle, by employing both perfect and imperfect successive interference cancellation (SIC) at nearby vehicle user. Furthermore, we present the asymptotic OP behavior at high signal-to-noise ratio (SNR) regime to gain deeper insights into the diversity order of NOMA vehicles. The findings reveal that the nearby vehicle under perfect SIC and far vehicle experience a diversity order of Nπ4256−π2, which is the function of number of reconfigurable elements (N) in the STAR-RIS. Whereas, a zero diversity order is obtained for nearby user under imperfect SIC case. Moreover, we analytically discuss the high SNR slopes of EC for both user vehicles. Furthermore, Monte-Carlo simulations are conducted to validate our analytical results under various channel and system parameter configurations. We also provide a comparison between the proposed scheme and STAR-RIS based orthogonal multiple access and cooperative relaying systems.

Measurement-based V2V propagation modeling in highway, suburban, and urban environments

Vehicle-to-vehicle (V2V) communication is one of the promising communication applications designed to optimize traffic conditions and has played a crucial role in the improvement of intelligent transportation technologies. Since there is still some uncertainty regarding generalized models that provide a more accurate representation of propagation environments, the existing literature emphasizes the need for additional experimental studies in various countries and propagation environments. This study aims to investigate the low-density and high-density characteristics of V2V channels for highway, suburban, and urban propagation environments in Türkiye. Thus, first, channel measurements were conducted for all propagation scenarios. Then, after the estimation of path loss parameters, the best-fitted path loss model was determined for each propagation scenario by comparing log-distance, two-ray, and log-ray models. It was observed that the log-ray model offered remarkably better performance than the two-ray model, especially in the majority of scenarios with two-ray characteristics. In addition, small-scale modeling and shadowing were also examined, and the outcomes were compared to relevant literature. Last, generalized path loss models were developed for six propagation scenarios and compared with previous studies. Providing additional experimental data on the impact of traffic and road environments that vary across countries on the V2V channel, this study not only validated and compared existing propagation models but also improved the representing accuracy and generalizability of the newly proposed propagation models. Here, all findings were presented in detail to support the motivation of the research.

A Mixed-Bouncing Based Non-Stationarity and Consistency 6G V2V Channel Model With Continuously Arbitrary Trajectory

A Mixed-Bouncing Based Non-Stationarity and Consistency 6G V2V Channel Model With Continuously Arbitrary Trajectory

An Improved GOMP Sparse Channel Estimation for Vehicle-to-Vehicle Communications

Reliable channel estimation is critical for wireless communication performance, especially in vehicle-to-vehicle (V2V) communication scenarios. Aiming at the major challenges of channel tracking and estimating as the highly dynamic nature of vehicle environments, an improved generalized orthogonal matching pursuit (iGOMP) is proposed for V2V channel estimation. The iGOMP algorithm transforms the channel estimation problem into a sparse signal recovery problem and replaces the classical inner product criterion with the Dice atom matching criterion. Additionally, the atomic weak progressive selection method is integrated to avoid the suboptimal selection of atoms from the redundant dictionary using the inner product criterion. The proposed iGOMP method can achieve optimal channel estimation by iterating feedback results. Simulation results demonstrate that the iGOMP method has superior estimation accuracy, mean square error (MSE), and bit error rate (BER) performance compared with traditional channel estimation methods in V2V communications.

Hybrid Far- and Near-Field Modeling for Reconfigurable Intelligent Surface Assisted V2V Channels: A Sub-Array Partition Based Approach

Reconfigurable intelligent surface (RIS)-assisted communications has been a hot topic due to its promising advantages for future wireless networks. Existing works on RIS-assisted channel modeling have mainly focused on far-field propagation condition with planar wavefront assumption. In essence, the far-field condition does not always hold because the RIS array dimension may be comparable to the terminal distance, especially in RIS-assisted mobile networks. To this end, we propose a hybrid far- and near-field stochastic channel model for characterizing a RIS-assisted vehicle-to-vehicle (V2V) propagation environment, which takes into account both far-field and near-field propagation conditions. To achieve the balance between the modeling accuracy and complexity for the investigation of the RIS-assisted V2V propagation characteristics, we develop a sub-array partitioning scheme to dynamically divide the entire RIS array into several smaller sub-arrays, which makes planar wavefront assumption applicable for the sub-arrays. Important channel statistical properties, including spatial cross-correlation functions (CCFs), temporal auto-correlation functions (ACFs), and frequency correlation functions (FCFs), are derived and investigated. Simulation results are provided to show the performance of the proposed sub-array partition based hybrid far- and near-field modeling solution for RIS-assisted V2V channels.

Event-Triggered Control with Intermittent Communications over Erasure Channels for Leader–Follower Problems with the Combined-Slip Effect

In this article, we investigate the vehicle path-following problem for a vehicle-to-vehicle (V2V)–enabled leader–follower scenario and propose an integrated control policy for the following vehicle to accurately follow the leader’s path. We propose a control strategy for the follower vehicle to maintain a velocity-dependent distance relative to the leader vehicle while stabilizing its longitudinal and lateral dynamics considering the combined-slip effect and tire force saturation. In light of reducing wireless communication errors and efficient usage of battery power and resources, we propose an intermittent V2V communication in which transmissions are scheduled based on an event-triggered law. An event is triggered and a transmission is scheduled in subsequent sample time if some of the well-defined path-following error functions (relative distance error and lateral error) exceed given tolerance bounds. Considering that the V2V communication channel might be erroneous or a transmission fails due to, e.g., vehicles’ distance or low battery power, we consider data loss in the V2V channel. Our proposed control law consists of two components: a receding horizon feedback controller with state constraints based on a safe operation envelop and a feedforward controller that generates complementary control inputs when the leader’s states are successfully communicated to the follower. To mitigate the effects of data loss on the follower’s path-following performance, we design a remote estimator for the follower to predict the leader’s state using its on-board sensor equipment when an event is triggered but the corresponding state information is not received by the follower due to a packet loss. Incorporating this estimator allows the follower to apply cautionary control inputs knowing that the path-following error had exceeded a tolerance bound. We show that while the feedback controller stabilizes the follower’s dynamics, the feedforward component improves the safety margins and reduces the path-following errors even in the presence of data loss. High-fidelity simulations are performed using CarSim to validate the effectiveness of our proposed control architecture specifically in harsh maneuvers and high-slip scenarios on various road surface conditions.

Channel modeling for V2V communication: Enhancing road safety and intelligent transportatio

The advancement of the Internet of Things (IoT) and Vehicle-to-Vehicle (V2V) communication networks has led to increased research efforts toward developing efficient and innovative V2V communication systems. These systems are designed to achieve the goal of improving road safety and enabling intelligent transportation. A critical aspect of this effort is channel modeling. In this context, this paper summarizes the characteristics of V2V communication channels. It categorizes them into three main types: Deterministic models, Non-geometry stochastic models (NGSMs), and Geometry-based stochastic models (GBSMs). It then reviews recent literature on these three types of channel modeling methods and discusses future development directions and challenges for V2V channel modeling. The study highlights the importance of accurate channel modeling for successful V2V communication systems and emphasizes the need to consider the unique features of V2V channels. It also identifies the limitations of existing channel models and suggests areas of research that can lead to more reliable and efficient V2V communication systems.

Maximal Ratio Combining Detection in OFDM Systems with Virtual Carriers Over V2V Channels.

This paper examines the performance of orthogonal frequency division multiplexing (OFDM) systems for vehicle-to-vehicle (V2V) communication channels. More specifically, a doubly selective channel under high intercarrier interference (ICI) is considered. Current solutions involve complex detection and/or reduced spectral efficiency receivers. This paper proposes the use of virtual carriers (VC) in an OFDM system with a low-complexity maximal ratio combining (MRC) detector to improve the bit error rate (BER) performance. The results show that VC provides diversity in received data, resulting in a ≥5 dB gain compared to previous OFDM systems with conventional linear/nonlinear detectors used as a reference. The detector presented in this paper has linear complexity, making it a suitable solution for real-time V2V communication systems.

Efficient Index Modulation-Based MIMO OFDM Data Transmission and Detection for V2V Highly Dispersive Channels

Vehicle-to-vehicle (V2V) communication networks are based on vehicles that wirelessly exchange data, traffic congestion, and safety warnings between them. The design of new V2V systems requires increasingly energetically and spectrally efficient systems. Conventional multiple-input–multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems have been used successfully for the last decade. However, MIMO-OFDM systems need to be improved to face future communication networks in high-mobility environments. This article proposes an efficient index modulation (IM)-based MIMO-OFDM system for V2V channels. The proposed transmission system is evaluated in high Doppler-spread channels. The results demonstrate that the proposed scheme reduces the required computational complexity in data detection and exhibits gains of up to 3 dB in bit error rate (BER) performance when compared to the conventional MIMO-OFDM system under the same conditions and parameters, along with achieving superior spectral efficiency. The results show the viability of implementing the proposed system in practical applications for high-transmission-rate V2V channels.

Dynamic V2V Channel Measurement and Modeling at Street Intersection Scenarios

Vehicular communication has been widely concerned by academia and industry. Wireless channel characterization and modeling are the foundation of communication systems. Compared with typical road scenarios such as urban and suburban areas, wireless channel characterization in intersections is a challenging task. In this paper, channel measurements at 5.9 GHz in street intersection scenarios are carried out and provide data for the characterization and modeling of time-varying vehicular channels. This paper proposes a double-slope path loss model, which can accurately reflect the signal propagation loss at intersections. Further, the time-varying spatial characteristics of multipath are extracted and analyzed, and the azimuth and elevation spread of arrival are statistically characterized. The influence of obstacles on multipath spatial characteristics in intersection scenarios is investigated. Then we investigate the spatial stationarity of channels and analyze the possible reasons for the differences in spatial stationarity of different scenarios. In addition, based on multipath extraction, we quantitatively analyze the energy of dense multipath components in different propagation scenarios. The research in this paper can enrich the investigation of vehicular channels and enable the analysis and design of vehicular communication systems.

Heterogeneous VLC/RF multi-hop cluster V2V channel allocation algorithm based on equivalent SINR.

To address low communication quality and limited transmission rate between vehicle nodes in the vehicularad hoc network (VANET), this paper builds a heterogeneous visible light communication (VLC) and radio frequency (RF) communication multi-hop communication model based on vehicle node clustering, and then a heterogeneous VLC/RF multi-hop cluster vehicle-to-vehicle (V2V) channel allocation algorithm based on equivalent signal to interference plus noise ratio (SINR) (NCAABES) is presented. This algorithm is based on the clustering of vehicle nodes, which introduces the concept of equivalent SINR. The equivalent SINR of the VLC channel between the cluster head (CH) and cluster member (CM) is used as the condition for channel allocation. When the channel between CH and CM is blocked or low quality, the neighboring vehicle between two vehicles is used as a relay node to communicate in a multi-hop way, and the channel with the best SINR is chosen as the current CH-CM or CM-CM communication method. The simulation results show that the SINR of NCAABES in this paper increases by 21.73%, 30.23%, and 70.96% compared to the novel multi-hop clustering scheme based on the weighted virtual distance detection (MCSVDD), the VLC network (VLCnet), and the RF network (RFnet), respectively. And the NCAABES's bit error rate (BER) is always the lowest compared to MCSVDD, VLCnet, and RFnet, even when the number of vehicles and transmission power change. This algorithm can improve the quality of communication between vehicle nodes, make VANET more efficient, and get a higher transmission rate.

A Multi-Resolution Channel Structure Learning Estimation Method of Geometry-Based Stochastic Model With Multi-Scene

Vehicle-to-vehicle (V2V) communication is the most typical application of the Internet of Vehicles, and it has many envisaged applications, such as driverless driving, collision warning and addressing traffic congestion. The realization of future intelligent transportation systems (ITSs) will require V2V communication technology, which in turn relies on accurate V2V channel estimation. As the possibilities that 5G technologies can be used for V2V communications are increasingly being explored, corresponding channel models used to describe the characteristics of V2V channels are also being updated, so the new channel estimation algorithms needed to be developed. Although the channel estimation method based on Convolutional Neural Network (CNN) has achieved remarkable success in communication problems in recent years, it cannot be well adapted to V2V channels under different scenarios and different modeling methods. In this article, a method is proposed for learning and estimating the channel structure in the 5G NR downlink that can adapt to the V2V channel under multi-scenes. The inherent block sparsity characteristics of the channel structure is adopted to combine the group lasso Alternating Direction Method of Multipliers (ADMM) algorithm with CNN, and residual dense network is employed to estimate and refine the V2V channel structure. Furthermore, the classifier and interpolation with pooling method are used to estimate the V2V channel structure under multi-scene and multi-resolution. Simulation results show that the performance of this method is better than other deep learning based estimation algorithms.

Envelope distribution and Doppler spectrum of V2V channels at 5.9 GHz in mountainous roads

Land transportation of people and goods often relies on strategic routes that pass through mountains. Despite the importance of these routes, the characteristics of the vehicular radio communication channel in such environments have received little attention. To close the gap, this paper presents the results of a measurement campaign at 5.9 GHz in mountainous roads. Data collected during the measurement campaign were used to quantify the envelope distribution and Doppler spectrum of small-scale vehicle-to-vehicle (V2V) communication channels. The measurements were taken in three different locations, two in San Luis Potosí (SLP), México, and one near Provo, Utah, USA. The locations in SLP are shrubland areas, whereas that in Utah is a coniferous forest. The diverse mountainous environments observed during the experiments were classified into five reference propagation scenarios. For each reference scenario the empirical channel envelope distribution was computed and compared with previously-published theoretical models based on the Rice, Nakagami, Weibull, and Gamma distributions. The Rice model provided the best fitting in 72.3% of the analyzed cases, whereas the Nakagami, Weibull and Gamma distributions were the best option in the remaining 11.3%, 14.9% and 1.3%, respectively. Likewise, the empirical distributions of the instantaneous mean Doppler shift (IMDS) and instantaneous Doppler spread (IDS) were computed. The results show that the IMDS follows the Generalized Extreme Value and Logistic distributions, whereas the Birnbaum-Saunders, Exponential, Burr and Nakagami distributions are proper models for the IDS. Our analysis also shows that the line-of-sight (LOS) path is the dominant factor for V2V communication in mountainous terrain, especially in roads surrounded by rocky structures with sparse vegetation. However, the contribution of non-LOS paths is not negligible, and it appears capable of supporting short intervals of communication. The results presented here can be used as guidelines for the analytical modeling and computer simulation of small-scale V2V channels in mountainous environments.

A Non-Stationary 6G V2V Channel Model With Continuously Arbitrary Trajectory

In this article, a novel three-dimensional (3D) massive multiple-input multiple-output (MIMO) millimeter wave (mmWave) geometry-based stochastic model (GBSM) is proposed for sixth-generation (6G) vehicle-to-vehicle (V2V) channels. In the proposed GBSM, clusters in the environment are divided into static clusters and dynamic clusters. Furthermore, the time-variant acceleration together with the integration of time during the transmission distance update are exploited. As a result, the continuously arbitrary trajectory of the transceiver and dynamic clusters is successfully captured. To jointly model space-time-frequency (S-T-F) non-stationarity of 6G V2V channels, a new method, which properly integrates the frequency-dependent factor, birth-death (BD) process, and selective evolution of static and dynamic clusters, is developed. Key channel statistics, including the space-time-frequency correlation function (STF-CF), time stationary interval, and Doppler power spectral density (DPSD) are obtained. Simulation results demonstrate that S-T-F non-stationarity is modeled and the impacts of vehicular traffic density (VTD) and vehicular movement trajectory (VMT) on channel statistics are further analyzed thoroughly. Finally, the generality and accuracy of the proposed GBSM are validated through the comparison of simulation results and available measurement data.

A Non-Stationary 3D-GBSM V2V Channel Model for Wideband Massive MIMO Systems

This letter presents a non-stationary 3D-GBSM vehicle to vehicle (V2V) channel model in tunnel environment based on massive multiple-input multiple-output (MIMO) antenna arrays. Instead of plane wavefront assumptions used in traditional MIMO systems, the proposed channel model considers spherical wavefront assumption for V2V communications. Firstly, the channel impulse response (CIR) and closed-form expression for probability density function (PDF) of angle-of-departure (AoD) and angle-of-arrival (AoA) in elevation and azimuth planes are derived. Afterwards, the expressions for the spatial cross-correlation function (S-CCF) and doppler power spectrum density (DPSD) due to the non-stationarity of transmitting (NT) and receiving (MR) antenna arrays are derived by considering different time separation, antenna arrays spacing, moving velocity, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -factor for line of sight (LoS) and non-line of sight (NLoS) propagation paths. The statistical characteristics of the proposed V2V wideband massive MIMO model are validated by measurement, analytical, and simulation results, verifying the effectiveness and adaptability of the proposed model in high-speed train (HST) environment.

V2V channel modeling at 5.2 GHz for highway environment

To design and evaluate vehicle-to-vehicle (V2V) communication systems in intelligent transportation system (ITS), it is important to understand the propagation mechanisms and channel models of V2V channels. This paper aims to analyze the channel models at 5.2 GHz for the highway environment in obstructed line-of-sight (OLoS) and line-of-sight (LoS) scenarios, particularly the vehicle connectivity probability derivation based on the propagation model obtained from measurement. First, the path loss (PL), shadow fading (SF), narrowband K-factor, and small-scale amplitude fading are analyzed. Results showed that the received signal magnitude follows Rice and Weibull distribution in LoS and OLoS scenarios, respectively. Second, we develop simple and low-complexity tapped delay line (TDL) models with a 10 MHz bandwidth for LoS and OLoS scenarios; in addition, we investigate the wideband K-factor, the root mean square delay spread (RMS-DS), and delay-Doppler spectrum. Third, we derive the closed form connectivity probability between any two vehicles in the presence of Weibull fading channel, and analyze the effects of Weibull fading channel and traffic parameters on connectivity. It is found that Weibull fading parameter, transmit power and vehicle density have positive impact on connectivity probability, PL exponent has negative impact on connectivity probability.

A geometry-based stochastic scattering channel model for V2V communications in dense urban street environments

In this paper, we propose a stochastic channel model in three-dimensional (3D) space for multiple input multiple output (MIMO) vehicle-to-vehicle (V2V) communications in dense urban environments. The movement of the mobile transmitter and mobile receiver results in the V2V channel model behave temporal non-stationarity. Therefore, the time-varying parameters of the propagation paths and angles are derived to characterize such property. Using this channel model, we investigate the propagation characteristics of V2V channels in terms of the road section and moving time/directions/speeds of the transmitter and receiver. Numerical results show that the theoretical results of the propagation characteristics of the V2V channel model are very close to those of the simulation ones, which show that the proposed channel model is suitable for depicting the V2V communications in dense urban scenarios.

Novel Optical Scattering-Based V2V Communications With Experimental Analysis

Taking advantage of the proliferation of optical wireless communications, this paper proposes a new paradigm of optical scattering (or ultraviolet) vehicle-to-vehicle (V2V) communication with experimental analysis based on extensive channel measurements at a wavelength of 266 nm. This new optical scattering-based V2V technology can ease a fundamental requirement of pointing, acquisition, and tracking (PAT) commonly found in conventional optical V2V systems and can also provide an additional robust capability of efficient non-line-of-sight (NLOS) V2V transmission. Based on the experiments, it is demonstrated that in a mobile V2V channel where the dynamics are changing rapidly, the scattering of the UV photons in the upper atmosphere produces some unique characteristics, resulting in greater randomness and severe fading. From the experimental results, we characterize the channel by a non-stationary time-frequency-selective fading channel with a statistical description of the time-frequency-varying power profile. An examination of the measured data reveals that the distribution of the fading statistics follows the Rayleigh distribution but a departure from the Rayleigh distribution is also observed. In addition, to facilitate the real-time capture of the dynamic behavior of the UV-based V2V channel, a Kalman filter-based algorithm is presented to estimate the time-varying optical scattering channel parameters. Finally, some open issues and challenges in the optical scattering-based V2V technology are presented.

Novel AoD Estimation Algorithms for WSSUS and Non-WSSUS V2V Channel Modeling

In this paper, we propose efficient computational solutions for estimating the statistical properties of wide-sense stationary un-correlative scattering (WSSUS) and non-WSSUS multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) channel models. Specifically, in the WSSUS channel models, we first estimate the angle of departure (AoD) for the non-line of sight (NLoS) propagation components. In this manner, the complex channel impulse response (CIR), which are widely used in the existing literature to characterize the wireless channel physical properties, can be estimated on the basis of the estimated AoD and defined model parameters. Conversely, in the non-WSSUS channel models, by estimating the AoD in the initial stage, the real-time complex CIR of the V2V channel model can be estimated on the basis of the estimated AoD and the moving time/velocities/directions of the mobile transmitter (MT) and mobile receiver (MR). In the estimation process of the aforementioned cases, we introduce different solutions to convert the CIRs from the complex domain to the real-value domain, thereby optimizing the computational efficiency for investigating channel characteristics as compared to existing methods. Numerical results of the WSSUS and non-WSSUS MIMO V2V channel characteristics, such as the spatial-temporal (ST) cross-correlation functions (CCFs) and auto-correlation functions (ACFs), are estimated on the basis of the estimated complex CIRs. These results are in agreements with theoretical ones, indicating that the proposed algorithms are practical for estimating the WSSUS and non-WSSUS MIMO V2V channel characteristics.

Non-stationary time-varying vehicular channel characteristics for different roadside scattering environments

With the deep integration of wireless communication technology and automobile industry, vehicular communication has become one of the key technologies supporting the development of Internet-of-vehicle. Due to the high-speed mobility of vehicles and the rapid change of the propagation environments, vehicle-to-vehicle (V2V) wireless communication channels are generally non-stationary. Meanwhile, the variability of V2V channel characteristics is obvious in different scattering environments. Focusing on these research points, this paper presents the analysis and comparison of V2V channel characteristics for different scattering scenarios based on a series of 5.9 GHz channel measurements. The measurement data are collected from the iron bridge, the soundproof wall, and the road lamp scenarios. The stationary time and frequency are investigated on the basis of method of local scattering functions. The classical channel characteristics, including power delay profile, Ricean K-factor, root means square (RMS) delay spread and RMS Doppler spread are extracted following the propagation principle. Furthermore, considering the source and birth-death process of multi-path components (MPCs) in different scattering propagation environments, cluster identification and statistical results are presented and compared. The different values of the channel parameters and the different performance of the channel under different scattering environments can help us understand the V2V channel deeply. The research results can be used for the design and optimization of vehicular communication systems in different scattering environments.