• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4123-4144
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• 2016

Vehicular Ad Hoc Networks (VANETs) utilize radio propagation models (RPMs) to predict path loss in vehicular environment. Modern urban vehicular environment contains road infrastructure units that include road tunnels, straight roads, curved roads flyovers and underpasses. Different RPMs were proposed in the past to predict path loss, but modern road infrastructure units especially flyovers and underpasses are neglected previously. Most of the existing RPMs are computationally complex and ignore some of the critical features such as impact of infrastructure units on the signal propagation and the effect of both static and moving radio obstacles on signal attenuation. Therefore, the existing RPMs are incapable of predicting path loss in flyovers and underpass accurately. This paper proposes an RPM to predict path loss for vehicular communication on flyovers and inside underpasses that considers both the static and moving radio obstacles while requiring only marginal overhead. The proposed RPM is validated based upon the field measurements in 5 GHz frequency band. A close agreement is found between the measured and predicted values of path loss.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1933-1954
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• 2013

Multiple wireless devices are being widely deployed in Intelligent Transportation System (ITS) services on the road to establish end-to-end connection between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) networks. Vehicular ad hoc networks (VANETs) play an important role in supporting V2V and V2I communications (also called V2X communications) in a variety of urban environments with distinct topological characteristics. In fact, obstacles such as big buildings, moving vehicles, trees, advertisement boards, traffic lights, etc. may block the radio signals in V2X communications. Their impact has been neglected in VANET research. In this paper, we present a realistic and efficient radio propagation model to handle different sizes of static and moving obstacles for V2X communications. In the proposed model, buildings and large moving vehicles are modeled as static and moving obstacles, and taken into account their impact on the packet reception rate, Line-of-sight (LOS) obstruction, and received signal power. We use unsymmetrical city map which has many dead-end roads and open faces. Each dead-end road and open faces are joined to the nearest edge making a polygon to model realistic obstacles. The simulation results of proposed model demonstrates better performance compared to some existing models, that shows proposed model can reflect more realistic simulation environments.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.4
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• pp.7-13
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• 1992

Diffraction loss occurs when the propagation path is obstructed by mountains and hills between a base station antenna and a moving vehicle antenna in mobile-radio communication. In this paper an approximate mathematical model using Fresnel-Kirchhoff diffraction theory is considered to predict propogation attenuation by natural obstacles with lateral profiles having general shapes. Field tests are conducted using helical and crossed drooping dipole antenna at 820 MHz. The theoretical analysis used in estimating the effects of hills agrees reasonably with experimental data. The results seem to be useful for estimating the level of received power, the minimum allowable input power, the optimum site of base station and consequently, planning terrestrial microwave links.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.300-308
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• 2012

Many indoor location tracking technologies have been proposed. Generally indoor location tracking using TOA signal is used, there is a weak point that it's difficult to track the location due to obstacles like a refraction, reflection and dispersion of radio wave. In this paper, we apply ETOA(Estimated-TOA) algorithm in NLOS(Non-Line-Of-Sight) environment to solve above problem. In NLOS environment, TOA value between Beacon and Mobile node is predicted by ETOA algorithm and the tracking of indoor location is also possible to identify using two NLOS beacons of three beacons by this algorithm. We show that the proposed algorithm is accurate location tracking is accomplished using the applying the proposed algorithm to indoor moving robot and the inertia sensor of robot and Kalman filter algorithm.