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Wireless Personal Communications

, Volume 97, Issue 3, pp 3861–3874 | Cite as

Evaluating Experimental Measurements of the IEEE 802.11p Communication Using ARADA LocoMate OBU Device Compared to the Theoretical Simulation Results

  • Aymen SassiEmail author
  • Yassin Elhillali
  • Faiza Charfi
Article
  • 235 Downloads

Abstract

Research interest has been focused on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems, known as V2X technologies, namely in road safety and traffic ergonomics. The evaluation of their performance is crucial before their potential integration and deployment in real systems. The present work aims at investigating the correspondences between two sets of scenarios of a simulation and an experimental model pertaining to the performance of IEEE 802.11p communication standard, and confronting their results. Concerning the first set, it pertains to the simulation of the physical layer PHY IEEE 802.11p standard, involving the implementation of V2X PHY transmission model, in a vehicle-to-vehicle V2V and vehicle-to-infrastructure V2I, according to different scenarios. The simulation series also involved data exchange between high-speed vehicles over Rice Race channel. This paper highlights several main parameters that may affect the physical layer network performance and the quality of transmission QoT. In this paper, the Bit Error Rate BER according to the Signal to Noise Ratio SNR was used to assess the performance of the V2X communication standard using all modulation types. Regarding the second set of evaluation scenarios, it includes the development of real-case measurements using the Arada LocoMate OBU transmission system to test the effects of the transmission range on V2X communications. V2I and V2V communications are evaluated in terms of real low and high mobility effects with transmission being taken into account.

Keywords

Vehicular communication WAVE IEEE 802.11p Vehicle to vehicle communication Vehicle to infrastructure communication OBU LocoMate equipment Experiments measurements 

1 Introduction

Owing to the continuous increase in the demand for mobility and transportation worldwide, the need to develop practicable solutions to reduce traffic congestion and improve road safety has become vital. Given the infrastructural and financial concerns, it has been reported that the construction of new roads constitutes an unattractive solution. Actually, the development of more efficient transportation systems is among the alternative solutions, which uses existing means, i.e. the vehicle and infrastructure, to lower traffic congestion, increase mobility and enhance safety. That is why the development of the Intelligent Transportation Systems (ITS) emerged as a new trend of research. These systems support cooperative communication systems incorporating intelligence not only in the vehicles but also the surrounding elements in the roadway infrastructure. Therefore, all over the world (Japan, America, Europe, etc.), researchers have recently been interested in vehicular communication, endeavoring to search for practical solutions to manage traffic flow, monitor road conditions, and improve road safety.

Vehicular communication is based on ITS and involves two different classes of applications, the first of which is road safety and the other is transport ergonomics. Vehicle-to-X (V2X) communication takes account of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, which in turn cover the transmission of information on several traffic parameters, including traffic lights, signs, lanes, sidewalks, and several other road structures. The efficient exchange of information between vehicles, on the one hand, and between vehicles and road infrastructure, on the other, entails the transmission and reception of important road-related data. The latter would allow modern vehicles to free the driver from complex and difficult tasks, and exchange information in interaction with their environment to detect and manage possible hazards on the road.

Most importantly, through standardized technology known as Wireless Access in the Vehicular Environment (WAVE) or the IEEE 802.11p communication standard, the IEEE community has incessantly been working on the amelioration of V2X communication. It highlights both the physical layer PHY specifications for the Dedicated Short Range Communication (DSRC) and the Medium Access Control (MAC) of vehicular communication. In view of the promising opportunities the aforementioned standardized technology may offer for the mitigation of traffic congestion and improvement of road safety, this work was undertaken to introduce a Matlab-based set of simulations for the V2X communication. The latter is associated with the IEEE 802.11p communication standard and complemented with a real-world experimentation using an ARADA Systems LocoMate OBU multimodal communication device. The obtained results from the two sets of evaluation scenarios pertaining to the performance of the IEEE 802.11p communication standard were compared.

The first suggested set of evaluation scenarios involves V2X PHY layer model making use of clustering models on diverse propagation environments. Several MATLAB simulations are performed using the proposal from the PHY layer 802.11p to analyze different Orthogonal Frequency Division Multiplexing (OFDM) modulation performance according to the vehicles mobility and the type of the channel transmission. As for the second set of evaluation scenarios, it aims to assess the real performance of the IEEE 802.11p system. A cluster of experimentation measurements was conducted at different environments to evaluate the Wireless Access in Vehicular Environment (WAVE) transmission in various scenarios. The objective of the first scenario is to determine the maximum range in which the communication between the sender and receiver can be accomplished. With respect to the second scenario, it aims at evaluating the communication between the infrastructure, embodied in a stopping vehicle and a vehicle moving at a different speed. The last scenario uses two vehicles moving at different speeds in opposite directions to evaluate V2V communication at high speed rates. To the best of our knowledge, this research work is the first to report on and demonstrate the consistency between a Matlab-based simulation and real-world experimentation involving the IEEE 802.11p communication standard.

The remainder of the paper are structured as follows. Section 2 reviews previous related works on the evaluation of the performance of the IEEE 802.11p communication standard. As for Sect. 3, it describes the transmission process architecture of this standard, with several operational parameters being taken into account. Besides, the scenarios and results from the first Matlab-based simulation sets are given in Sect. 4. Then, the experimental materials and methods, including the hardware and set of scenarios used in our study, are presented in Sect. 5 which will also describe the experimental results and conclusions emanating from the data. Finally, Sect. 6 provides a summary and a set of future perspectives.

2 Related Works

One of the most important areas of research seeking to enhance the quality of transport, Intelligent Transportation Systems (ITS) emerges, taking into account the existing public infrastructure into account. They are systems based on new communication techniques associated with V2X communication. Indeed, their performances, including those involving MAC and/or PHY layer performances, have been tested by several research studies.

In Jafari et al. [1], the IEEE 802.11p standard have been analysed and a set of measures in an NS-2 network simulator has been implemented using a realistic model based on vehicular mobility. Their simulation scenarios have focused on the throughput, End-to-End delay, and Packet Loss Ratio (PLR) to highlight the impact of mobility and packet size on the WAVE standard. The results of their research work revealed the same probability of successful message reception when the distance is less than 138 m for all vehicles used. They came to the conclusion that the average of the throughput and the End-to-End delay metrics increase with the increase of the message sizes.

As regards Park et al. [2], they have undertaken the study of the constrained impact of packet size on vehicular networks. To find a solution to this limitation, they have based their analysis on the transmission rate according to a different data set and based on length size to optimize the IEEE 802.11p transmission quality.

In the study of Eichler et al. [3], the performance of the Wireless Access in Vehicular Environment (WAVE) has been evaluated using a set of evaluation simulations that took several parameters, such as collision probability and delay, into account. The authors concluded that WAVE can prioritize messages, and in dense and heavy scenarios, the delay would significantly increase, whereas the throughput would decrease.

Simulating the IEEE 802.11p MAC protocol for the V2I communication was also the fundament of Wang et al. [4] ‘s research work. The NS-2 simulation results showed that owing to the backoff time size, the used protocol may have a poor throughput performance. The authors have suggested two different approaches to overcome this problem and improve the MAC protocol under dense and dynamic conditions. As regards the first approach, it is a centralized approach that is capable to calculate the ideal backoff window size according to the exact number of transmitting vehicles. With respect to the second one, it is a distributed approach, in which vehicles are able to use local observations to adjust the window size.

Furthermore, a measurement field of 802.11p communication technology on track experimentation was the attempt of both Sassi et al. [5] and Demmel et al. [6]. In fact, they have elaborated on some of the metrics, such as maximum range, packet loss rate, and other speed impacts. Their findings illustrate that the transmission quality decreases with the growth of the range, and when speed grows up to 50 km/h, the PLR becomes worst for all tested modulations.

Based on time-domain estimation, Lin et al. [7] have proposed a method to pass by the insufficient bandwidth coherence for channel estimation according to a rich scattering. Actually, it is through the application of the Least Square algorithm assisted by Zadoff-Chu sequence on both the preamble field and the cyclic prefix that the enhancement was proven in their work.

Paier et al. [8] reported on an outdoor V2I trial based on the IEEE 802.11p PHY protocol. They have found that the measurement results on highway are the average downstream performance, thus confirming that the vehicles shadowing effects can cause a fluctuating performance, especially when using a long size packet with high vehicle mobility.

Maier et al. [9], in their turn, have presented the results of the performance evaluation of a multi-antenna receiver based on the IEEE 802.11p communication standard. Their assessment involved real world measurements associated with the Selection Combining (SC), Equal Gain Combining (EGC), and Maximum Ratio Combining (MRC) algorithms. Their findings have revealed that although the poor receiving conditions may be poor, reliability and robustness can be substantially improved. Indeed, they have reported that the frame success ratio raised up to 25%.

The focus of the research work of Zhao et al. [10] was on the analysis of channel estimation schemes devoted to the inter-vehicular communication systems. A new channel estimation scheme based on pilot symbols was proposed by these authors by changing data symbols into pilot ones. Their estimation was confirmed to be able to enhance the standardized scheme in high SNR, which is clearly seen in the analysis and simulation results.

Sukuvaara et al. [11] have based their study on experimenting the inter-vehicular communication performances. Actually, both IEEE 802.11p standard and 3G cellular network for test measurements have been paired, in an attempt to study an intelligent traffic safety system using a V2I communication architecture. Based on both measurement fields and pilot deployment, they have proposed a realistic system deployment strategy for simple scenarios, indicating that the use of pilot system can properly provide defined services. These authors came to the conclusion that the utilization of such hybrid method could lead to a encouraging solution for the eventual commercial system.

In addition, the future exploitation of V2X communication in urban environments have been explored by Gozalvez et al. [12] who have conducted a set of V2I measurements based on the IEEE 802.11p standard, trying to highlight the impact of urban characteristics and infrastructure transmission unit conditions. Their results have revealed that several parameters, namely traffic density, the presence of heavy vehicles, and field altitude, have to be taken into consideration for optimal transmission.

The amelioration of the performance of the IEEE 802.11p communication can also be accomplished by using multiple antennas. Indeed, Fernández-Caramés et al. [13] described the design and implementation of such technique based on two IEEE 802.11p software transceivers and two FPGA channel emulators. The WAVE communication has been proven to be considerably improved through the use of the MIMO system. They reported that compared to the standard, the performance evaluation could be accelerated from 6 to 209 times. Paier et al. in [14] have oriented the evaluation of the PHY layer in the V2I communication standard, by performing a set of real world measurements along a highway road and considering various scenarios involving different data rates, packet lengths, and vehicle speeds. The height of the mounted antenna has been proven to affect the quality of transmission. They evaluated communication performance with a OBU speed of 120 km/h, revealing that speed can seriously deteriorate transmission. In fact, the results found in [14] illustrate that the frame error rate worsened up to 0.1.

The authors in [15] have been interested in measuring the real performance of the IEEE 802.11p using NEC Link Bird-MX fixed on two different vehicles. They have discussed the results of the WiSafeCar project and estimated the V2V communication system capacity on real world environment. The main result found in this work pertains to the fact that the IEEE 802.11p performance was higher than the general performance using traditional Wi-Fi. They have suggested the use of cellular network (3G) with the IEEE 802.11p as a hybrid communication technique for future use.

Gozalvez et al. [16] have conducted many testing campaigns in the context of a European project: iTETRIS. The main problem of their study was the evaluation of V2I performance using RSU utilization in an urban environment. Several parameters, including street layout, field height, heavy traffic, and surrounding trees, were found to be influential factors for better transmission. The obtained results using DENSO WSU elucidate the effect of the range on the packet delivery ratio.

Finally, the Maier et al.’s work [9] has underlined the evaluation of IEEE 802.11p performance using Kapsch TrafficCom equipment in their experimentations based on the study of V2I communication. The three different combining techniques used in their analysis were the Selection Combining (SC), the Equal Gain Combining (EGC), and the Maximum Ration Combining (MRC). The impact of the message length on the frame error ration was the main results highlighted by the authors, indicating that the larger frames lead to significantly increased error probabilities.

To offer best improvement for inter-vehicular communications, a comprehensive performance evaluation is required. The overview of the previous studies shows that they were either experimental or theoretical, but no studies has focussed on their comparison. Works that have proposed techniques to improve performance WAVE were not based this real case situation. Therefore, we propose a V2X performance survey based on IEEE 802.11p comparison between real-world experimental measurements and theoretical results.

3 IEEE 802.1p PHY Layer Transmission Model

The encoding process of the IEEE 802.11p used in our work consists of several complex steps illustrated in Fig. 1. A detailed description of the procedure convergence is provided in the following overview [17, 18, 19].
Fig. 1

Transmitter process for 802.11p study

Since there is no relation with the upper layer, a data source component is used to generate the transmitted bits. The data are scrambled in order to avoid the presence of long bit sequences that can lead to errors during transmission. The data source scrambling component produces a sequence of 127 bits based on the following function (1):
$${\text{S}}\left( {\text{x}} \right) = {\text{x}}^{7} {\text{ + x}}^{4} { + 1}$$
(1)

A convolutional encoder is employed at a ½ coding rate to avoid potential undesirable effects induced by the Inter-Symbol Interference ISI and Inter-Carrier Interference ICI on the generated data and to detect and correct errors. It is also used to assure the addition of redundancy to the transmitted bit stream.

The output of convolutional encoder is equipped with a puncturing element to produce upper coding rates of R = 3/4 and R = 2/3. The puncturing decreases the number of bits to be transmitted and, consequently, increases the coding rate. It involves the omission of some of the coded bits on the transmitter side and their substitution by “zeros” in the convolutional decoder on the receiving side. The puncture model is specified by the binary puncturing vector which corresponds to two bit sequences: 1110 for rate R = 2/3 and 110,101 for rate R =3/4.

The coded data are interleaved to avoid error bursts induced by channel fading. The interleaving process consists of a two-step permutation in time and frequency domains. The first permutation seeks to ensure that no two successive bits are coded in two adjacent subcarriers. The second permutation guarantees that two successive bits are alternately represented in the most and least significant bits of the constellation employed.

The modulation of the interleaved data is performed by the phase shift keying (BPSK or QPSK) or amplitude modulation (16-QAM or 64-QAM). The throughput of the transmitted signal is affected by the selection of the mapping and coding rate, ranging between 3 Mb/s (with BPSK and 1/2 coding rate) and 27 Mb/s (with 64-QAM and 3/4 coding rate). The bit streams are converted into symbols for simultaneous transmission. Accordingly, the OFDM technique is used to convert the serial data stream into various parallel ones. The Inverse Fourier Transform (IFT) technique is also applied to modulate those data onto orthogonal subcarriers. The total number of existing subcarriers is 64, but only 52 information carriers are used for mapping. In fact, the application of the 11 guard subcarriers on the OFDM spectrum sides aims to provide separation from adjacent sub-bands. This step involves the positioning of the complex symbols associated with different constellation points on subcarriers. The 52 subcarriers used in the IEEE 802.11p were composed of 48 data subcarriers and 4 pilot subcarriers. The pilot subcarriers are used to ensure the robustness of detection against frequency offsets and phase noise; the pilot symbols are used to identify the channel and observe the changes introduced to the transmitted signal. The pilot subcarriers are inserted in subcarriers −21, −7, 21 and 7. The OFDM symbols are converted from the frequency to the temporal domain using IFFT so as to transport the data on subcarriers.

A second GI1 is introduced before each OFDM symbol to avoid the occurrence of ISI and ICI problems due to by multipath propagation. The IEEE 802.11p (Draft 9.0) [18] defines the GI1 duration as being equal to \({\text{TGI}}_{1} { = }\frac{\text{TFFT}}{4}\). It consists in copying the end of the OFDM symbol in the beginning of the symbol that follows. The IEEE 802.11p transmission process is illustrated in Fig. 1 [18].

4 Matlab Simulation and Real-World Experimentation: Scenarios and Results

4.1 Scenarios

The scenarios used in this study focused on both simulation and real-world experiments. They involved two complementary fields, namely the IEEE 802.11p real-world performance and the dedicated WAVE model consistency, where the Matlab simulator and experiments were considered.

4.1.1 Matlab Simulation Scenarios

This section describes the design of multiple simulations aiming to evaluate the performance of inter-vehicle communication. All cases aimed to investigate the variance of the QoT, particularly the SNR effect. Two different approaches are performed, the first of which consists in studying the V2I and the second one deals with the V2V. The simulation conditions consider the same number of symbols in a transmitted frame (1000 symbols). A comparative study is performed for each type of modulation, depending on whether the vehicles are moving in an urban or a stopped setting. According to the modulations allowed by the standard, eight different data rates were investigated (3, 4.5, 6, 9, 12, 18, 24, 27 Mbits/s). Since it provides both direct and reflected links between the sender and receiver, the Rician radio channel is used to simulate the urban environment. The scenarios involve different speed factors applied according to their dependence on the Doppler Shift variance. Three sets of simulations are carried out. The first set aims to evaluate the performance of the V2X communication with speed equal to 0. The second set considers a moderate speed ranging from 0 to 50 km/h. The third set of scenarios deals with a higher speed that can reach up to 260 km/h [18].

4.1.2 Real World Experimentation Scenarios

The different scenarios carried out are based on real-world experimental testing using an ARADA Systems LocoMate OBU, a multimodal communication device compliant with the IEEE 802.11p communication standard. The Arada Systems LocoMate is a leading developer of technologies for vehicle-based communication network applications, including tools collection, vehicle safety services, and commerce transactions via cars. LocoMate has been extensively evaluated for real-time communication between vehicles and roadside access points or other vehicles creating a real-time public safety network [20]. The Arada Systems LocoMate OBU device can provide wireless communication in a vehicular environment while considering different data rates according to the IEEE 802.11p standard. It offers low latency connectivity for both inter-vehicle and vehicle to roadside units. This solution integrates a GPS device for vehicle navigation. Figure 2 shows the Arada LocoMate OBU and the 5.9 GHz antennas used in our experiment.
Fig. 2

Landing runway of an unused Cambrai airfield

Figure 3 illustrates that the experimental scenarios of this study were performed on a 1.5-km-long landing runway of an unused Cambrai airfield. The tests involved the use of two vehicles equipped with Arada LocoMate OBU devices according to the same 8 data rates and the same packet length. The tests drew special attention to the effects of the receiving signal quality Received Signal Strength Indication (RSSI), data rate, distance between the sender and the receiver and vehicle speed. Packets are dumped from a monitor interface that has the ability to obtain different MAC layer parameters on the sender, including the measurement results of the Packet Lost Ratio (PLR) and RSSI. The results are collected at 10,000µ second intervals between two successive packets.
Fig. 3

Fixed scenarios area

4.2 Results and Discussions

Our simulation and experimental results can be grouped into three areas of interest. The first set of results concerns the impact of the signal to noise ratio on the quality of transmission. The second relates to the effect of moderate speed mobility on V2I communication performance. The third cluster of results pertains to the effect of high speed mobility on V2 V communication.

4.2.1 Agreement Between Simulation and Experimentation Data in Relation to SNR Effects on Transmission Quality

The first area of interest is about the agreement of SNR effect on the QoT for both simulations and experiments. Simulations were performed according to the eight different possible modulations.
$$SNR = \frac{{P_{r} }}{{P_{noise} }}$$
(2)
In order to represent the relation between the SNR (2) and the distance between sender and receiver, we have used the Friis transmission Eq. (3):
$$\frac{{P_{r} }}{{P_{t} }} = G_{t} *G_{r} *\left( {\frac{\alpha }{4\pi D}} \right)^{2}$$
(3)
where G t and Gr refer to the transmission antenna and reception antenna gain, respectively, D to the range between the sender and receiver, and \(\alpha\) to the wave length as given in (4):
$$\alpha = \frac{v}{f}$$
(4)
where v refers to the phase velocity magnitude and f to wave frequency.
From our set of experimentations, it can be concluded that only the D range will change. Accordingly, the SNR value decreases in the same way that the range D grows as illustrated in (5):
$$SNR = \frac{{P_{t} * \varphi }}{{P_{noise} *D^{2} }}$$
(5)

The first field of experiment tests were carried out to evaluate the maximum connectivity range of the IEEE 802.11p. Two vehicles were employed with the distance between them ranging from 100 to 1000 m. The first Vehicle was considered as a transmitter and the second as a receiver.

Figure 4a illustrates the dependence between the ratio SNR and the BER: vertical axes show BER whereas horizontal axes show SNR.
Fig. 4

a Impact of SNR on the BER for different modulations with Matlab simulation [18]. b Impact of range on the PLR for different modulations with real world experimentation

Figure 4b shows the PLR obtained for the first scenario. As illustrated in the 8 different curves (related to the 8 modulations of the WAVE standard), the PLR is noted to degrade sharply when the distance between the sender and receiver decreases.

The findings from this first scenario revealed that the 1000 m theoretical maximum range in the IEEE 802.11p standard can be supported only in low data rates of 3 and 4.5 Mbits/s. A high data rate can, however, be used (18, 24 and 27 Mbits/s) when the vehicles are close to each other (<200 m). These results can be attributed to the quality of the received signal which is noted to improve when the transmission power is fixed and the distance communication range is reduced. The results from this experiment also indicate that the more the data rate is increased, the worse the PLR values become, reaching 0, 1.8, and 45% with 3, 12, and 27 Mbits/s, respectively, for the 200 m’ range. We can conclude that the decrease of the range presented in Fig. 4a corresponds to the increase of the SNR shown in Fig. 4b.

We can, therefore, conclude that the attainment of efficient connection, particularly if the sender vehicle is far from the receiver vehicle (more than 200 m), requires the application of a low data rate. By compiling all curves in plots, the QoT is shown to increase with better levels SNR (the Range decreases).

4.2.2 Agreement Between Simulation and Experimentation Data with Regard to the Impact of Mobility on V2I

The second simulation set aimed to study the V2X communication by considering an urban environment where the relative speed cannot exceed 120 km/h. We can conclude that mobility is an important factor in V2X communication. It is noted that as the speed increases (from 50 to 90 km/h) the BER increases (from 2.3 10-2 to 9.5 10-2) for the best OFDM modulation BPSK ½.

The second set of experiments aimed to evaluate the real performance of V2I communication. Accordingly, we considered a first stopping vehicle as a sender Access Router (AR, Roadside Unit) and a second one as a receiver Mobile Router (MR, Vehicle) using different speeds ranging from 10 to 110 km/h. As shown in Fig. 3, we have fixed the same starting point for the MR to keep the same measurement conditions in all iterations.

The findings from this comparative analysis confirm that the curve shapes generated in our Matlab- based simulation matched relatively well with the evolution of the curves modelled in the experimental system. The effect previously observed for the increase of the data rate on the PLR can also be observed in Fig. 5a, b below. Different speeds are considered in this scenario.
Fig. 5

a Impact of mobility on V2I with Matlab Simulation (speed 20–120 km/h) [18]. b Impact of mobility on V2I communication with real world experimentation (speed from 20 to 110 km/h)

Figure 5a shows the relationship between the PLR and the speed variation of V2I communication. The curves show that the PLR becomes worse with the increase of the speed level until reaching a reasonable sight from 10 to 110 km/h. This result can presumably be ascribed to the Doppler shift.

4.2.3 Agreement Between Simulation and Experimentation Results with Regard to the Impact of Mobility on V2V

In the third simulation scenarios, we tried to evaluate V2X communication for the different modulations while considering a relatively high speed (from 10 to 260 km/h). We can note that high mobility exerts negative effects on the QoT: the findings illustrated in Fig. 6a, b show that when the speeds reach 190 km/h, the 8 modulation curves become more and more close to each other according to speed growth. Nevertheless, the BPSK½ seems to be the best modulation type.
Fig. 6

a Impact of high mobility on V2V communication with Matlab simulation (speed from 20 to 260 km/h) [18]. b Impact of mobility on V2I communication with real world experimentation (speed from 20 to 220 km/h)

The third scenario was undertaken to evaluate the real WAVE performance in the V2V condition. The maximum speed employed in this scenario was 220 km/h. The relative speed concept was used, with the two vehicles employed moving in opposite directions at a speed varying from 10 to 110 km/h so as to obtain a relative speed ranging from 20 to 220 km/h. Figure 3 indicates that, as in the V2I scenario, the same starting transmission point was delimited in this experiment for the two vehicles. The packet reception performance was then obtained at the reception unit.

The results presented in Fig. 6b show the impact of the high speed range according to the PLR on V2 V communication. These results provide interesting practical insights that can be summarized as follows: the application of low data rates induces more important effects of node mobility on vehicular communication than higher data rates. Moreover, and according to the results presented in Fig. 6a, b, a 5–11.5% increase in PLR can be obtained for data rates of 3 and 27 Mbits/s at 50 km/h, respectively. Last but not least, the more the node speed increases, the worse the quality of transmission becomes: for the BPSK½, the PLR increases from 6–18% for 40 km/s and 220 km/h, respectively. We can finally conclude that both Fig. 6a, b are in agreement with their curves shapes.

To deepen the performance study of the inter-vehicular communication, we proposed to perform experimental tests on different types of roads and paths. In this framework, we have divided the topologies into two other scenarios, the first of which concerns the urban environment, cities and agglomerations, while the second one deals with rural roads. Due to road safety reasons and failing governmental consent, we were obliged to postpone this experimental phase. Indeed, in the context of an European project, we will continue our tests on the closed circuit Transalley which is a dedicated technology park for STIs in Valenciennes university campus. This Transalley loop will reproduce the majority of possible routes topologies.

5 Conclusions and Perspectives

The present work aimed to design a set of Matlab-based simulations for V2X communication in relation with the IEEE 802.11p communication standard and a further set of real-world experimentations using the ARADA Systems LocoMate OBU multimodal communication device. The correlations between the findings from the two sets of evaluation scenarios with regard to the performance of the IEEE 802.11p communication standard are investigated. The results obtained reveal that the use of low data rate is preferred for better performances in the case of long-range communications. The findings also show that communications can be negatively affected by node mobility. Furthermore, the experimental data indicate that, in the case of V2 V communication, the more the node speed grows, the worse the quality of transmission becomes. In fact, for BPSK ½ modulation, when the node speed increases from 20 to 220 km/h, the PLR degrades from 0 to 18%, respectively. The major insight obtained from this work suggests that communications at high data rate are required in potential applications of the system under investigation and that further efforts are needed to improve the performance of communications taken at high mobility.

Overall, the compilation of the results from the simulation and real-world experimentation indicate that the implemented model helped to achieve a relatively good description of the real communication involved in our inter-vehicular communication. Considering the promising results and conclusions yielded by our model, further studies, some of which are currently underway in our laboratory, are needed to optimize this standard based on intelligent and dynamic solutions using an assisted decision method.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.LETI/ENISUniversity of Sfax, ENISSfaxTunisia
  2. 2.IEMN/UVHCUVHCValenciennesFrance

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