The vehicle-to-vehicle (V2V) propagation channel has significant implications on the design and performance of novel communication protocols for vehicularad hocnetworks (VANETs). Extensive research efforts have been made to develop V2V channel models to be implemented in advanced VANET system simulators for performance evaluation. The impact of shadowing caused by other vehicles has, however, largely been neglected in most of the models, as well as in the system simulations. In this paper we present a shadow fading model targeting system simulations based on real measurements performed in urban and highway scenarios. The measurement data is separated into three categories, line-of-sight (LOS), obstructed line-of-sight (OLOS) by vehicles, and non-line-of-sight due to buildings, with the help of video information recorded during the measurements. It is observed that vehicles obstructing the LOS induce an additional average attenuation of about 10 dB in the received signal power. An approach to incorporate the LOS/OLOS model into existing VANET simulators is also provided. Finally, system level VANET simulation results are presented, showing the difference between the LOS/OLOS model and a channel model based on Nakagami-mfading.

In this paper, a deterministic channel model for vehicle-to-vehicle (V2V) communication is compared against channel measurement results collected during a V2V channel measurement campaign using a channel sounder. Channel metrics such as channel gain, delay and Doppler spreads, eigenvalue (EV) distribution, and antenna correlations are derived from the ray-tracing (RT) simulations as well as from the measurement data obtained from two different measurements in an urban four-way intersection. The channel metrics are compared separately for line-of-sight (LOS) and non-LOS (NLOS) situations. Most power contributions arise from the LOS component (if present) as well as from multipaths with single bounce reflections. Measurement and simulation results of the received power show a very good agreement in the presence of LOS, as most of the received power is carried by the LOS component. In NLOS, the difference is large because the ray-tracer is unable to capture some of the channel characteristics due to the underlying limitations of our ray-based propagation model. Despite the limitations, the model is suitable to characterize some, but not all, of the channel properties in a sufficient manner. We find that the diffuse scattering and multibounced nonspecular reflections must be considered for an accurate prediction of the channel in such a rich scattering environment.

This paper presents the results of an empirical study of wireless propagation channels for vehicle-to-vehicle communications in street intersections, a scenario especially important for collision avoidance applications. The results are derived from a channel measurement campaign performed at 5.6 GHz in four different types of urban intersections. We present results on typical power delay profiles, pathloss and delay spreads and discuss important propagation mechanisms. By comparing the results of the different intersections, we find that absence of line-of-sight is problematic for system coverage, especially when there are few other significant scattering objects in and around the intersection. Roadside buildings can create important propagation paths that account for a considerable part of the total received power.

Two strong technology trends, one in the mobile communications industry and the other in the automotive industry, are becoming interwoven and will jointly provide new capabilities and functionality for upcoming intelligent transport systems (ITSs) and future driving. The automotive industry is on a path where vehicles are continuously becoming more aware of their environment due to the addition of various types of integrated sensors. At the same time, the amount of automation in vehicles increases, which, with some intermediate steps, will eventually culminate in fully automated driving without human intervention. Along this path, the amount of interactions rises, both in-between vehicles and between vehicles and other road users, and with an increasingly intelligent road infrastructure. As a consequence, the significance and reliance on capable communication systems for vehicleto-anything (V2X) communication is becoming a key asset that will enhance the performance of automated driving and increase further road traffic safety with combination of sensor-based technologies [1].

This paper focuses on capabilities enabled by 5G connectivity in the cooperative, connected and autonomous cars, and elaborates on two technical enablers. One of the technical enablers consists of a beamformed broadcast/multicast technology that builds on adaptive and robust beam management techniques at the air interface. The other proposed technical component aims to improve the end-to-end architectural design of 5G networks to enable efficient broadcast and multicast transmissions for vehicle-to-anything services. Finally, the key results of multicast and broadcast technical components are described and ongoing and future areas of work and research are detailed.

Shadowing from vehicles can significantly degrade the performance of vehicle-to-vehicle (V2V) communication in multilink systems, e.g., vehicular ad hoc networks (VANETs). It is, thus, important to characterize and model the influence of common shadowing objects like cars properly when designing these VANETs. Despite the fact that for multilink systems it is essential to model the joint effects on the different links, the multilink shadowing effects of V2V channels on VANET simulations are not yet well understood. In this paper, we present a measurement-based analysis of multilink shadowing effects in a V2V communication system with cars as blocking objects. In particular, we analyze, characterize, and model the large scale fading, both regarding the autocorrelation and the joint multilink cross-correlation process, for communication at 5.9 GHz between four cars in a highway convoy scenario. The results show that it is essential to separate the instantaneous propagation condition into line-of-sight (LOS) and obstructed LOS (OLOS), by other cars, and then apply an appropriate pathloss model for each of the two cases. The choice of the pathloss model not only influences the autocorrelation but also changes the cross correlation of the large scale fading process between different links. By this, we conclude that it is important that VANET simulators should use geometry-based models, that distinguish between LOS and OLOS communication. Otherwise, the VANET simulators need to consider the cross correlation between different communication links to achieve results close to reality.