Highway and rural propagation channel modeling for vehicle-to-vehicle communications at 5.9 GHz

Cheng, Lin; Henty, B.E.; Bai, Fan; Stancil, Daniel D.

doi:10.1109/aps.2008.4619037

Cited by 52 publications

(44 citation statements)

References 2 publications

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“…Similar results were reported by Kunisch and Pamp [31], who used a power law model for highway and urban environments; but found a two-ray model best suited for rural environments. The measurements of Cheng et al [25,32] suggested that a break point model is suitable to describe the V2V path loss. The results in [33], obtained from the empirical measurements of the IEEE 802.11p communications channel, under normal driving conditions in rural, urban and highway scenarios justified the use of classical power law model for V2V path loss.…”

Section: Related Workmentioning

confidence: 99%

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Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels

Chandrasekharamenon

AnchareV

2012

J Wireless Com Network

118

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Vehicular ad hoc network (VANET) is a type of promising application-oriented network deployed along a highway for safety and emergency information delivery, entertainment, data collection, and communication. In this paper, we present an analytical model to investigate the connectivity properties of one-dimensional VANETs in the presence of channel randomness, from a queuing theoretic perspective. Connectivity is one of the most important issues in VANETs to ensure reliable dissemination of time-critical information. The effect of channel randomness caused by fading is incorporated into the analysis by modeling the transmission range of each vehicle as a random variable. With exponentially distributed inter-vehicle distances, we use an equivalent M/G/∞ queue for the connectivity analysis. Assuming that the network consists of a large number of finite clusters, we obtain analytical expressions for the average connectivity distance and the expected number of vehicles in a connected cluster, taking into account the underlying wireless channel. Three different fading models are considered for the analysis: Rayleigh, Rician and Weibull. The effect of log normal shadow fading is also analyzed. A distance-dependent power law model is used to represent the path loss in the channel. Further, the speed of each vehicle on the highway is assumed to be a Gaussian distributed random variable. The analytical model is useful to assess VANET connectivity properties in a fading channel.

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Section: Related Workmentioning

confidence: 99%

“…Recently, many researchers have paid much attention to V2V channel measurements, for understanding the underlying physical phenomenon in V2V propagation environments (ex: [24][25][26][27][28][29][30][31][32][33]). Analysis of probability density function (PDF) of received signal amplitude was reported in [24][25][26] for V2V systems.…”

Section: Related Workmentioning

confidence: 99%

Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels

Chandrasekharamenon

AnchareV

2012

J Wireless Com Network

118

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“…Some work has been done on measuring performance of legacy IEEE 802.11a/b/g in vehicular environments [6]. The only IEEE 802.11p measurement-based papers we are aware of are concerned with characterization of PHY layer parameters of the 5.9 GHz radio channel used by IEEE 802.11p, such as multi-path propagation [7], received signal strength [8], delay spread [5], and so on. In a recent paper [9], Paier et al investigate PHY layer performance of 802.11p infrastructureto-vehicle links, mostly evaluating the communication range (defined as the range up to which a percentage p of MAC frames can be correctly received).…”

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confidence: 99%

Measuring IEEE 802.11p Performance for Active Safety Applications in Cooperative Vehicular Systems

Martelli

Renda

Santi

2011

2011 IEEE 73rd Vehicular Technology Conference (VTC Spring)

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Abstract-In this paper, we present a measurement study of application layer performance in IEEE 802.11p vehicular networks. More specifically, our focus is on active safety applications, which are based on the exchange of beacon messages containing status information between close-by vehicles. We consider two performance metrics relevant to active safety applications: the first is application-layer goodput, which can be used to optimize congestion control techniques aimed at limiting the beaconing load on the wireless channel; the second is the beacon reception rate, which is useful to estimate the level of situation awareness achievable onboard vehicles. Our measurements were conducted using a prototypal, 802.11p compliant communication device developed by NEC, in both stationary and mobile V2V scenarios, and disclosed several useful insights on 802.11p application-level performance. To the best of our knowledge, the ones presented in this paper are the first application-level measurements of IEEE 802.11p based vehicular networks reported in the literature. I. INTRODUCTIONGiven their potential of considerably reducing car accidents and improving traffic conditions, active safety applications are of primary importance in vehicular networking. This explains the extensive interest this class of applications has gathered in the research and industry community. Despite these intensive efforts, active safety application performance has been mostly evaluated through analysis and simulation. This is mainly due to the fact that the IEEE 802.11p standard for short range vehicular communications, upon which active safety application will be built, is still in draft form. Thus, 802.11p compliant hardware is still difficult to find, and often turns out to be rather expensive.To the best of our knowledge, no application-level IEEE 802.11p measurement study has been reported in the literature so far.

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“…The model is empirical with parameters obtained from hardware measurements over a vehicle-to-vehicle wireless channel in a suburban environment. The model is extended in [23] for a vehicle-to-vehicle highway scenario. The small scale fading is modeled using a correlateddistance varying Nakagami-m distribution whose severity (the value of m) changes based on the time-varying distance between the sender and the receiver [22].…”

Section: Effect Of Physical Channel Impairmentsmentioning

confidence: 99%

Delay Analysis for Sparse Vehicular Sensor Networks with Reliability Considerations

Abdrabou

Liang

Zhuang

2013

IEEE Trans. Wireless Commun.

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-This paper addresses the relation between message delivery delay and reliability for the communication between a vehicle and a road side unit (RSU). We focus on sparse vehicular sensor networks (VSNs), where timely message delivery and reliable transmission are of significant importance. We present a mathematical framework for the message delivery delay distribution for a two-lane road, where vehicles in one direction act as message carriers for the ones in the other direction and have the freedom to leave the road from randomly distributed road junctions with a certain probability. Packet generator vehicles store the original packets till meeting an RSU while sending multiple copies of each packet to packet carrier vehicles. Our analysis offers an analytical tool for an intelligent transportation system (ITS) service provider to determine the minimum RSU density required to cover a road for meeting a probabilistic requirement of the message delay.Extensive computer simulation results show the accuracy of our analysis and clearly indicate the relation of packet delay and the number of packet replicas.Index Terms -Delay, vehicular sensor networks, vehicle-to-infrastructure transmission, disrupted connectivity, road side unit placement, information delivery reliability.

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Highway and rural propagation channel modeling for vehicle-to-vehicle communications at 5.9 GHz

Cited by 52 publications

References 2 publications

Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels

Connectivity analysis of one-dimensional vehicular ad hoc networks in fading channels

Measuring IEEE 802.11p Performance for Active Safety Applications in Cooperative Vehicular Systems

Delay Analysis for Sparse Vehicular Sensor Networks with Reliability Considerations

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