Abstract
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.
Highlights
The intelligent transport system (ITS) is defined as the set of applications to provide innovative services for the transport of various modes and involve a wide range of different technologies and applications such as beam switching duringThe associate editor coordinating the review of this manuscript and approving it for publication was Amjad Mehmood .the overtaking process, dynamic traffic light sequence, and autonomous vehicles [1].In the ITS, the vehicular Ad-hoc Network (VANET) is envisaged as the most important component to realizing intelligent connected vehicles, which is incorporated in the following architectures: vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrians (V2P) and vehicle-to-everything (V2X) [2]
In the case of the ‘‘overtaking situation’’, we evaluate the multiple antennas and beam switching (Beam 1, 2, 3) techniques at the Rx; for the ‘‘various base station (BS) heights’’, we mainly study the impact of different BS heights on beam 2
RT SIMULATIONS FOR DIFFERENT CASES For both the urban and the highway scenarios, besides considering the multiple antennas and beam switching (Beam 1, 2, 3) at the vehicle user equipment (UE) in the different overtaking situations mentioned above and various BS heights, we have considered two different traffic flows:
Summary
The intelligent transport system (ITS) is defined as the set of applications to provide innovative services for the transport of various modes and involve a wide range of different technologies and applications such as beam switching during. Semi-autonomous and fully autonomous vehicles will require a high rate and low latency communication links to support the applications envisaged by the fifth-generation mobile communications (5G) Infrastructure Public Private Partnership’s These applications include the See-Through use case (maximum latency equal to 50 ms), which enables vehicles to share live video feeds of their onboard cameras to the following vehicles. The wireless industry is moving into the 5G and beyond the 5G era, which can achieve enhanced mobile broadband (eMBB), ultra-reliable and low-latency communications (uRLLC), and massive machine-type communication (mMTC) [13] This communication system will use the millimeter wave (mmWave) band, where a large number of spectrum resources are still underutilized, providing unprecedented spectrum and Gbit/s data rates to a mobile device, can support typical cellular communications, vehicular communications, accuracy position, and high-speed-train (HST) communications [14].
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