Propagation Aspects in Vehicular Networks

Rubio, Lorenzo; Reig, Juan; Fernández, Herman

doi:10.5772/15650

Cited by 10 publications

(15 citation statements)

References 55 publications

(54 reference statements)

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“…For each subpath measured, a linear relationship between the path loss, expressed in dB, and the logarithmic of the Tx-Rx separation distance can be established, in the same manner that the traditional fix-to-mobile (F2M) channels. Then the path loss, denoted by P L, is estimated by the following linear model [2,6]:…”

Section: A Methodologymentioning

confidence: 99%

“…New vehicular safety proposals based on the integration of information and communication technologies into both vehicles and infrastructure are being developed. These proposals have led to the intelligent transportation system (ITS) concept [1,2]. Some of these safety proposals require large-range vehicular communications systems.…”

Section: Introductionmentioning

confidence: 99%

“…In Europe, the European Telecommunication Standard Institute (ETSI) adopted the DSRC band for ITS applications assigning 50 MHz (from 5.875 GHz to 5.925 GHz). The special features of both safety and non-safety applications require to develop and implement new communication technologies, where one of the many challenges to be address is the characterization and modeling of the vehicular propagation channel [2][3][4][5][6]. Thus, the vehicular channel is at present an important area in channel modeling.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Path loss characterization in vehicular environments under LOS and NLOS conditions at 5.9 GHz

Fernández

Peñarrocha

Rubio

et al. 2014

The 8th European Conference on Antennas and Propagation (EuCAP 2014)

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Abstract-Based on a narrowband channel measurement campaign, this paper will characterize the path loss in vehicular environments under line-of-sight (LOS) and non-LOS (NLOS) at 5.9 GHz. Based on a linear slope model, values of the path loss exponent and the standard deviation of the shadowing will be reported in three different environments, i.e., urban with high road traffic density, urban with moderate/low traffic density, and expressway. The results presented here can be incorporated in an easy way into vehicular networks (VANETs) simulators to develop, evaluate and validate new protocols and systems architectures configurations under more realistic propagation conditions.

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Section: A Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Path loss characterization in vehicular environments under LOS and NLOS conditions at 5.9 GHz

Fernández

Peñarrocha

Rubio

et al. 2014

The 8th European Conference on Antennas and Propagation (EuCAP 2014)

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“…These proposals have led to the intelligent transportation system (ITS) concept. At present, different ITS applications have been introduced, such as variable message signs (VMS), located at strategic point (e.g., tunnels and merging highways) to inform drivers about traffic conditions and dangerous situations, navigation systems, cameras and short-range emergency systems [1,2]. Therefore, there are safety applications for distance emergency situations that required large-range vehicular communications systems.…”

Section: Introductionmentioning

confidence: 99%

Path Loss Modeling for Vehicular System Performance and Communication Protocols Evaluation

et al. 2013

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ValeroAbstract Vehicular communications are receiving considerable attention due to the introduction of the intelligent transportation system (ITS) concept, enabling smart and intelligent driving technologies and applications. To design, evaluate and optimize ITS applications and services oriented to improve vehicular safety, but also non-safety applications based on wireless systems, the knowledge of the propagation channel is vital. In particular, the mean path loss is one of the most important parameters used in the link budget, being a measure of the channel quality and limiting the maximum allowed distance between the transmitter (Tx) and the receiver (Rx). From a narrowband vehicular-to-vehicular (V2V) channel measurement campaign carried out at 5.9 GHz in three different urban environments characterized by high traffic density, this paper analyzes the path loss in terms of the Tx-Rx separation distance and fading statistics. Based on a linear slope model, values for the path loss exponent and the standard deviation of shadowing are reported. We have evaluated the packet error rate (PER) and the maximum achievable Tx-Rx separation distance for a PER threshold level of 10% according to the digital short-range communications (DSRC) specifications. The results reported here can be incorporated in an easy way to vehicular networks (VANETs) simulators in order to develop, evaluate and validate new protocols and systems architecture configurations under realistic propagation conditions.

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“…Probabilistic (stochastic) model determines the physical characteristics of the vehicular channel in a totally stochastic manner without making presumptions for any underlying geometry [19]. In stochastic modelling technique, the distance-dependent path loss, largescale and small-scale fading distributions are the major parameters that need to be estimated in the stochastic model [20]. In this technique, the path loss is representative of the local mean received signal power, a relative function of the transmit power is a function of the total distance between the receiver and the transmitter.…”

Section: B-probabilistic Channel Modelmentioning

confidence: 99%

A predefined channel coefficients library for Vehicle-to-Vehicle communications

Al-Khalil

Turner

Al-Sherbaz

2015

2015 7th International Workshop on Reliable Networks Design and Modeling (RNDM)

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-It is noticeable that most of VANETs communications tests are assessed through simulation. In a majority of simulation results, the physical layer is often affected by an apparent lack of realism. Therefore, vehicular channel model has become a critical issue in the field of intelligent transport systems (ITS). To overcome the lack of realism problem, a more robust channel model is needed to reflect the reality.

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Propagation Aspects in Vehicular Networks

Cited by 10 publications

References 55 publications

Path loss characterization in vehicular environments under LOS and NLOS conditions at 5.9 GHz

Path loss characterization in vehicular environments under LOS and NLOS conditions at 5.9 GHz

Path Loss Modeling for Vehicular System Performance and Communication Protocols Evaluation

A predefined channel coefficients library for Vehicle-to-Vehicle communications

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