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Routing and data diffusion in VANETs -- Signal disturbance

January 30, 2018

January 30, 2018

Editor's Note: Wireless sensor networks lie at the heart of emerging applications in nearly every industry segment. In building these networks, designers contend with issues that encompass real-time communications, efficient high-bandwidth data exchange, multiple network topologies, selection of optimal routing strategies, and more. The book, Building Wireless Sensor Networks, offers detailed treatments on critical requirements and promising solutions in each of these areas and more. 

This excerpt focuses on design challenges and methods associated with creating a vehicular ad hoc network (VANET). To share data as vehicles pass on roads or rest in parking areas, a VANET must contend with issues as varied as the physics of signal propagation, the fluid nature of data routing, and the security vulnerabilities associated with participation in an ad hoc network. Because of the changing nature of a VANET, designers need a broad understanding of these issues. 

In this excerpt from the book, the authors offer an in-depth discussion that defines the nature of VANET challenges and discusses alternatives for their solution. Continuing the description of VANETs begun in part 1, this installment of this series provides an in-depth discussion of the four main effects responsible for signal disturbance. 

Elsevier is offering this and other engineering books at a 30% discount. To use this discount, click here and use code ENGIN318 during checkout.

Adapted from Building Wireless Sensor Networks, by Smain Femmam, Editor.

 

Chapter 3. Routing and data diffusion in vehicular ad hoc networks
By Frédéric Drouhin and Sébastien Bindel

3.2.2.1. Path loss

In a perfect environment, electromagnetic waves are only affected by the frequency and the distance between the transmitter and the receiver. In such an environment, no obstacles are present between stations, and it is denoted as free space. Let Gt be the transmission gain, Pt the power of the transmitted signal, and W the power density at a distance d, which is computed as follows according to [PAR 00]:

From the relationship between W and Pr the received signal power, equation [3.3] can be formulated as follows:

with Ar the effective aperture of the received antenna, λ the wavelength and Gr the reception gain. From equations [3.2] and [3.3], the [FRI 46] equation determines the signal attenuation in a free space environment:

The Friis equation describes a vanilla environment and can be considered suitable for describing a signal propagation in far field environments. Regarding the ground environment and the position of the antennas, the propagation loss model described by Friis can be improved by taking into account the signal reflection on the ground. This model is called a two ray ground and describes the line of sight component and the multi-path component (ground reflection) of the received signal. According to [RAP 01], for a very large distance d and a perfect polarization and reflection, the calculation of the received signal power Pr can be formulated according to the equation [3.5].

with ht and hr the height of the transmitter and receiver antenna and L the system loss and fixed at 1 according to [3.5]. A common strategy adopted by network simulators is to use the two-ray ground model, equation [3.5], when the distance d is larger than a cross-over distance dc and a free-space model, equation [3.4], in the other case:

Friis and the two-ray ground model are not suitable for describing dense environments, such as urban or building environments. A common model adopted for describing such environments is the log-distance model, where the path loss L at a distance d is expressed as follows:

with L0 the reference path loss value based on measurement made at distance d0. A close version of this model applies three consecutive log-distance models with different α coefficients according to the distance between the emitter and the receiver.

3.2.2.2. Large-scale shadowing

Large-scale shadowing, also called local mean attenuation, occurs due to the obstruction of the signal when it meets an obstacle such as a building, a truck or an hill. Confirmed by empirical studies in both indoor and outdoor environments, the most common model used is log-normal shadowing. It takes into account the path loss based on a reference distance d0 and applies a log-normal shadowing in order to compute the power reception ¬Pr(d) as follows:

with a typical value for β ∈ [2.7, 5] and χσ is a log-normal distribution with a standard deviation σdB ∈ [4, 12]dB in an outdoor environment.

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