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Radio access technologies (RATs) are a key topic in railways, enabling them a better service rendering in terms of shorter headways between trains, higher safety levels and higher customer satisfaction. Very often, these railway RATs need a lot of time to be developed, tested and put into service, which implies a lack of efficiency and bottlenecks in the evolution of railway systems. To solve this situation, an emulation platform that considers both the physical layer and the network (this is, able to emulate the end-to-end chain) is envisaged in the EmulRadio4Rail project. Therefore, the physical layer of many railway scenarios must be emulated, which is a remarkable challenge because railways are very diverse. We see Tapped-Delay Lines (TDL) models as the most efficient way for emulation with the available hardware. In the literature, there are many TDL-based channel models for all the scenarios we considered but one: tunnels. Therefore, in order to fill this gap, we develop a novel TDL model for railway tunnels, considering the impact of the rolling stock (both high-speed railway (HSR) and subway trains). The proposed model allows the full characterization of this scenario in terms of power-delay-profile (PDP), Doppler spectrum and fading characteristics.

Accurate path loss (PL) prediction is essential for predicting transmitter coverage and optimizing wireless network performance. Traditional PL models are difficult to cope with the development trend of diversity, time-varying and mass wireless channels. In this work, the most widely used multilayer perceptron (MLP) neural network in artificial neural network (ANN) is employed to accurately predict PL. Three types of environmental features are defined and extracted, which describe the propagation environment only by considering limited environmental types instead of complex 3D environment modeling. Principal component analysis (PCA) is used to generate the low-dimensional environmental features, and eliminate redundant information among similar environmental types. Moreover, the information of base station (BS) and the receiver (Rx), including 3D locations, frequency, the transmitted power of BS, the antenna information, the feeder loss, and the received power of all the locations are obtained from the measurements. Different environmental features are combined with the information of BS and Rx to construct seven datasets for PL prediction models based on MLP neural networks. The impacts of the number of neurons in the hidden layer, the number of hidden layers, the number of training samples, and environmental features on PL prediction models are explored by considering the absolute value of mean error (AME), the mean absolute error (MAE), the standard deviation (STD) of error, the correlation coefficient, and the time ratio, respectively. This work aims to understand the propagation characteristics of radio waves, which can provide a theoretical basis for wireless network optimization and communication system design.

In recent years, the intelligent transport system (ITS) has been developed rapidly because of global urbanization and industrialization, which is considered as the key enabling technology to improve road safety, traffic efficiency, and driving experience. To achieve these goals, vehicles need to be equipped with a large number of sensors to enable the generation and exchange of high-rate data streams. Recently, millimeter-wave (mmWave) technology has been introduced as a means of meeting such a high data rate requirement. In this paper, a comprehensive study on the channel characteristics for vehicle-to-infrastructure (V2I) link in mmWave band (22.1-23.1 GHz) for various road environments and deployment configurations is conducted. The self-developed ray-tracing (RT) simulator is employed with the calibrated electromagnetic (EM) parameters. The three-dimensional (3D) environment models are reconstructed from the OpenStreetMap (OSM). In the simulations, not only the vehicle user equipment (UE) moves, but also the other vehicles such as cars, delivery vans, and buses move around the vehicle UE. Moreover, the impacts of the receiver (Rx) multiple antennas and beam switching technologies at the vehicle UE are evaluated as well. The channel parameters of the V2I link in mmWave band, including received power, Rician $K$ -factor, root-mean-square delay spread, and angular spreads are explored in the target scenarios under different simulation deployments. This work aims to help the researchers understand the channel characteristics of the V2I links in mmWave band and support the link-level and system-level design for future vehicular communications.

With the challenge to form the networks of the Intelligent Transportation Systems (ITS), both technologies of vehicles and wireless communication are required to be connected tightly. In terms of wireless communication, the communication system in the terahertz (THz) frequency range with ultra-large bandwidth is a potential technology to support very high-data-rate wireless transmission at the age of beyond fifth-generation mobile communications (B5G). In this paper, the carrier frequency of 300 GHz with 8 GHz bandwidth vehicle-to-infrastructure (V2I) channel is characterized for the urban and highway scenario, respectively. The self-developed ray-tracing (RT) simulator is employed with the calibrated electromagnetic (EM) parameters. Since the wavelength of carrier frequency approaches the diameters of raindrops and snowflakes, the significant influence of the precipitation on the channel characterization is studied in our work as well. The large-scale parameters of the THz V2I channel, including path loss, Rician K-factor, root-mean-square (RMS) delay spread, and angular spreads are explored in the target scenarios under sunny, rainy, and snowy conditions, respectively. The channel characteristics studied in this paper can be used to support the link-level and system-level design for the future THz vehicular communications.

In the vision of intelligent transportation, vehicles are expected to feature with advanced applications, such as automatic road enforcement, dynamic traffic light sequence, and autonomous driving. Therefore, real-time and fast dynamic information exchanges are required, and vehicle-to-everything (V2X) communications are highly demanded. In this work, the channel characteristics of vehicular communication are analyzed in the millimeter-wave (mmWave) band at 22.1-23.1 GHz. Specifically, two types of links (the satellite link and the terrestrial link) are considered in urban and highway scenarios with different weather conditions. The ray-tracing simulator together with calibrated electromagnetic parameters is employed to practically generate wideband channels. The key channel parameters of each link including the received power, Rician K -factor, root-mean-square delay spread, and angular spreads are explored. The co-channel interferences between the two links are analyzed as well. The observations and conclusions of this work can be useful for the design of V2X communication technologies.