1. Introduction
The concept of Smart City is so broad and relatively immature that its scope is not yet fully defined. The main motivation behind this concept comes from the efficient use of the available resources [
1]. The implementation of the triad computing, communication and sensing can increase the efficiency levels significantly in several areas such as hydraulic resources, waste management, crime control, traffic management and transportation, among others. Within the different notions a Smart City should provide, Intelligent Transportation Systems (ITS) emerge as a promising idea to increase efficiency in fuel use, gas emission, route optimization and drivers’ safety.
In a world society where approximately 1.35 million people die annually in traffic-related accidents, which is the eighth leading cause of death for people of all ages and the first for people between 5 and 29 years old [
2], the use of ITSs could play an important role in the solution of this critical problem. Its approach to solving this scourge is to make vehicles go beyond human deficiencies, that means, vehicles with the ability to sense their surroundings and act accordingly. To achieve these goals more sensors will be incorporated into vehicles. In fact, it is estimated that in 2020 the number of built-in sensors will reach more than 200 and that internet-integrated vehicle applications will jump to 90% by these dates [
3,
4,
5]. The massive traffic of data produced by these sensors will require transfer rates in magnitudes of gigabits per second to communicate with other vehicles or road infrastructure. This capacity will allow bringing cloud computing to the era of autonomous driving [
6]. As a consequence, the demand for wireless techniques that support this high bandwidth has increased considerably in the past years. Wireless connectivity with high transfer rates is predicted to be the next frontier in the vehicular revolution.
Both the academy and the automotive industry are exploring reliable and efficient connectivity solutions. It is in this context that vehicle-to-everything (V2X) communication performs a key role, by means of sharing and collecting knowledge between intelligent elements (i.e., another vehicle, building or traffic light). The physical layer of these links is supported by standards such as IEEE 802.11p or Dedicated-Short-Range-Communication (DSRC). While these technologies ensure low latency (less than 10 ms), their theoretical transfer rate is limited up to 27 Mbps [
3,
7]. Nevertheless, in recent years, significant academic activity, motivated by these requirements, has proposed the adoption of millimeter-wave (mmWave) frequencies (i.e., 10–300 GHz) to support high transfer rates and low latencies [
8]. While the use of mmWave bands promises a significant increase in data rate with less latency, their use comes with a high cost of implementation. Wireless links at these high frequencies suffer from many deteriorating factors, high penetration loss, blocking and considerable path loss which pose challenges to the V2X communications. In addition to these limitations, the high medium mobility and the relatively low height of the transceivers also increase the Doppler effect phenomenon and occurrences of non-line-of-sight (NLOS). Therefore, achieving effective communication in mmWave links for vehicular environments requires a deep understanding of the vehicle communication channel, which is significantly different from those studied at frequencies below 6 GHz [
8].
In this work, we present the analysis of an urban V2X mmWave link scenario using an in-house Matlab-based ray-launching (RL) algorithm [
9]. The scenario description is presented in
Section 2, as well as the simulation parameters for two different frequency bands.
Section 3 shows the obtained results in terms of received power, power delay profile (PDP) and Doppler shift (DS). Finally, conclusions and future work are presented in
Section 4.
2. Scenario Description
This section describes the scenario used to model vehicular communication through the RL algorithm.
Figure 1 presents a view of the real scenario, located in a side street of Tecnológico de Monterrey, Campus Monterrey, Mexico and its rendered schematic view used for simulation. The modeled fragment corresponds to an area of approximately
m which has different types of vegetation within it, such as different trees and shrubbery. The portion corresponding to the avenue occupied by the vehicles has a length of 150 m and a width of 16.5 m, where a median strip with inhomogeneous vegetation and two lanes per driving direction are included, representing a classical urban complex heterogeneous vehicular scenario. The rest of the segment shows abundant vegetation and buildings with one to eight floors.
The modeled scenario is chosen for its usefulness in terms of communication environments between urban vehicles. The presence of a median strip with abundant trees constitutes an engaging scenario for communications between vehicles on different roads. It has been considered the realism of the stage, and the placement of elements such as luminaires, traffic lights and irregular people traffic.
The transmitter has been placed above a vehicle (see
Figure 2 for reference) located in the road at 1.5 m height. Two antennas have been used for the transmitter, each with 10 dBm of power. The first transmitter is a directional antenna with a beamwidth of 70 degrees, 20 dBi gain, and transmission frequency at 28 GHz. The second antenna has an omnidirectional radiation pattern with a gain of 0 dBi and a transmission frequency of 5.9 GHz. The use of different frequencies has been considered emulating the standard IEEE. 802.11p (DSRC) at 5.9 GHz and the mmWave communication at 28 GHz.
Table 1 shows the different simulation parameters.
4. Conclusions
This research analyzes some of the main characteristics of a vehicular link in a complex urban environment by means of an in-house developed 3D-RL algorithm. Two different frequency bands were analyzed, 5.9 GHz and 28 GHz. The blocking effect that occurs at mmWave frequency bands is presented. In addition, the received signal shows a marked contribution of the multipath components at both frequencies. Doppler shift was also analyzed, as it is a significant feature in communication systems with high mobility. Results obtained highlight the adverse effects that occur in the frequency shift for 5.9 GHz and 28 GHz, the latter most affected due to the reduction in wavelength. The analysis carried out, as well as the results obtained in the simulation, can lead to important considerations that need to be taken into account in order to provide proper characterization of vehicular communications in urban environments. Future work may be focused on a more extensive analysis over mmWave V2X communications, considering the blockage caused by medium and small size objects, as well as by vehicles of different dimensions and characteristics. In addition, a campaign of measurements will be performed in the real scenario, to validate the mmWave propagation channel characterization. These analyzed results and the proposed methodology can aid in an adequate design and implementation of next generation vehicular networks.