Pathloss and Multipath Power Decay of the Wideband Car-to-Car Channel at 5.7 GHz

Paschalidis, Panagiotis; Mahler, Kim; Kortke, Andreas; Peter, Michael; Keusgen, Wilhelm

doi:10.1109/vetecs.2011.5956721

Cited by 20 publications

(14 citation statements)

References 8 publications

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“…Previous studies reported similar values: = 2.9 by Durgin et. al in [29] (NLOSb environment) and 2.44   3.39 by Paschalidis et al in [42] (urban environment -various LOS conditions). Finally, for NLOSb links, we determine the received power as the maximum of the received power calculated by the implemented model (using eq.…”

Section: E Practical Considerations For Different Link Types and Promentioning

confidence: 98%

See 1 more Smart Citation

Geometry-Based Vehicle-to-Vehicle Channel Modeling for Large-Scale Simulation

Boban¹,

Barros

Tonguz

2014

IEEE Trans. Veh. Technol.

200

145

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Large-scale Vehicular Ad Hoc Network (VANET) simulators by and large employ simple statistical channel models. By design, such models do not account for specific objects in the region of interest when estimating the channel. While computationally efficient, these models were shown to be unable to provide satisfactory accuracy on a link level for typical VANET scenarios. Specifically, experimental studies have shown that both large static objects (e.g., buildings and foliage) as well as mobile objects (surrounding vehicles) have a profound impact on the quality of vehicle-to-vehicle (V2V) channels. While several recently proposed large-scale V2V channel models account for static objects (e.g., buildings) in the simulated area, there is a need for a comprehensive model that takes into account both the static and the mobile objects. To fill this gap, we designed a geometry-based, computationally manageable V2V channel model that uses the real-world locations and the actual dimensions of vehicles, buildings, and foliage to simulate the V2V channel more realistically. We use the outlines of the modeled objects to form spatial tree structures for efficient manipulation of geographic data. We distinguish and model separately the following three link types: line of sight (LOS), non-LOS due to vehicles, and non-LOS due to static objects. Apart from the model for large-scale signal variations, we also propose a simple model for small-scale signal variation using the number and size of the objects around the communicating vehicles. We validate the models against extensive measurements performed in urban, suburban, highway, and open space environment. We provide the complete simulation recipe for the implementation of the model in simulators. Finally, we implement the model in Matlab and show that it scales well by simulating networks with tens of thousands of objects and hundred thousand communicating vehicle pairs using commodity hardware.

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Section: E Practical Considerations For Different Link Types and Promentioning

confidence: 98%

“…For example, Paschalidis et al in [42] performed measurements in different environments (urban, suburban, rural, highway) and fitted the measurements data to the log-distance path loss model. The path loss exponent (PLE) varied considerably (between 1.83 and 3.59) for different locations and LOS conditions.…”

Section: Related Workmentioning

confidence: 99%

Geometry-Based Vehicle-to-Vehicle Channel Modeling for Large-Scale Simulation

Boban¹,

Barros

Tonguz

2014

IEEE Trans. Veh. Technol.

200

145

View full text Add to dashboard Cite

show abstract

“…At 5.9 GHz, our extracted values of the path loss exponent agree very well with previous works. In [8], [11] and [12] values of the path loss equal to 1.61, 1.68 and 1.83 have been measured in urban environments, respectively. In [7], [8] and [11] values of 2.1-2.5, 1.61 and 1.59 have been derived in suburban environments.…”

Section: Resultsmentioning

confidence: 99%

Path Loss Characterization for Vehicular Communications at 700 MHz and 5.9 GHz Under LOS and NLOS Conditions

Fernández

Rubio

Peñarrocha

et al. 2014

Antennas Wirel. Propag. Lett.

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In this letter we present a path loss characterization of the vehicular-to-vehicular (V2V) propagation channel. We have assumed a path loss model suitable for vehicular ad hoc networks (VANETs) simulators. We have investigated the value of the model parameters, categorizing in line-of-sight (LOS) and non-LOS (NLOS) paths. The model parameters have been derived from extensive narrowband channel measurements at 700 MHz and 5.9 GHz. The measurements have been collected in typical expected V2V communications scenarios, i.e., urban, suburban, rural and highway, for different road traffic densities, speeds and driven conditions. The results reported here can be used to simulate and design the future vehicular networks.

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“…While there are many sophisticated statistical models to describe multi-path fading in radio propagation (such as Rayleigh, Ricean, and Nakagami distributions), several studies have also shown that the two-ray ground reflection model, which considers both a direct propagation path and a ground reflection path, gives a good result for dedicated short-range inter-vehicle communications at 5.9 GHz band [24][25][26]. We adopt the following generalized log-distance path loss model to reproduce wireless links between the transmitter and receiver:…”

Section: Radio Propagation Modelmentioning

confidence: 99%

“…In vehicular communication scenarios, the path loss exponents ranging from 1.4 to 3.5 and from 2.8 to 5.9 have been reported in lineof-sight (LOS) and non-line-of-sight (NLOS) situations, respectively [24,25]. The wireless transmission range r 0 of each node can then be calculated as the equivalent transmission power using a receiving threshold, P rx,th , also referred to as the reception sensitivity.…”

Section: Radio Propagation Modelmentioning

confidence: 99%

Minimum node degree of k-connected vehicular ad hoc networks in highway scenarios

Xiong

et al. 2016

J Wireless Com Network

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A vehicular ad hoc network (VANET) is a specific type of mobile ad hoc networks (MANETs); it can provide direct or multi-hop vehicle-to-vehicle (V2V), vehicle-to-roadside (V2R), vehicle-to-pedestrian (V2P), and vehicle-to-internet (V2I) communications based on the pre-existing road layouts. The emerging and promising VANET technologies have drawn tremendous attention from the government, academics, and industry over the past few years and have been increasingly available for a large number of cutting edge applications that can be classified into road safety, traffic efficiency, and infotainment categories. Due to the unique characteristics of VANETs, such as high mobility with an organized but constrained pattern, and diverse radio propagation conditions, the conventional researches dedicated for general MANETs cannot be directly applied to VANETs. This paper presents an analytical framework to investigate the minimum node degree of k-connected VANETs, with a homogeneous range assignment in highway scenarios. We simulate the mobility patterns with realistic vehicular traces, model the network topology as a two-path fading geometric random graph, and conduct extensive experiments on the derived analytical results. Through a combination of mathematical modeling and simulations, we derive a probabilistic bound for the minimum node degree of a homogeneous vehicular ad hoc network in highway scenarios. The analytical framework is useful in the study of connectivity and estimation of performance in one-dimensional vehicular ad hoc networks.

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Pathloss and Multipath Power Decay of the Wideband Car-to-Car Channel at 5.7 GHz

Cited by 20 publications

References 8 publications

Geometry-Based Vehicle-to-Vehicle Channel Modeling for Large-Scale Simulation

Geometry-Based Vehicle-to-Vehicle Channel Modeling for Large-Scale Simulation

Path Loss Characterization for Vehicular Communications at 700 MHz and 5.9 GHz Under LOS and NLOS Conditions

Minimum node degree of k-connected vehicular ad hoc networks in highway scenarios

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