Comparison of Ray Tracing and Channel-Sounder Measurements for Vehicular Communications

Nuckelt, Jorg; Abbas, Taimoor; Tufvesson, Fredrik; Mecklenbräuker, Christoph F.; Bernadó, Laura; Kürner, Thomas

doi:10.1109/vtcspring.2013.6692484

Cited by 38 publications

(19 citation statements)

References 7 publications

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“…It is straightforward to add additional attributes to the XML descriptors of building definitions provided by Open Street Maps, including the material out of which each building is predominantly composed. The validity of this method has previously been established in [18]; the authors found the approach provided results in close agreement with those obtained by applying building data supplied by local government, especially in verifying channel sounder measurements with raytracing simulations [19].…”

Section: Building Geometry Datasupporting

confidence: 66%

Including general environmental effects in K-factor approximation for rice-distributed VANET channels

Cooper

Mukunthan

Safaei

et al. 2015

Physical Communication

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a b s t r a c tThis paper presents a method of approximating the Rician K -factor based on the instantaneous static environment. The strongest signal propagation paths are resolved in order to determine specular and diffuse powers for approximation. The model is experimentally validated in two different urban areas in New South Wales, Australia. Good agreement between the model and experimental data was obtained over short-range communication links, demonstrating the suitability of the model in urban VANETs. The paper concludes with recommendations for methods to account for vehicles in the simulation and incorporating additional phenomena (such as scattering) in the approximation. Crown

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Section: Building Geometry Datasupporting

confidence: 66%

Including general environmental effects in K-factor approximation for rice-distributed VANET channels

Cooper

Mukunthan

Safaei

et al. 2015

Physical Communication

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“…The simulations were done for the same urban intersections as where the measurements were performed. In [14] the analysis was limited to a single-input single-output (SISO) antenna configuration and a comparison was made only in terms of power delay profile (PDP) and path loss metrics.…”

Section: Introductionmentioning

confidence: 99%

Simulation and Measurement-Based Vehicle-to-Vehicle Channel Characterization: Accuracy and Constraint Analysis

Abbas

Nuckelt

Kürner

et al. 2015

IEEE Trans. Antennas Propagat.

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Abstract-In this paper, a deterministic channel model for vehicle-to-vehicle (V2V) communication, is compared against channel measurement data collected during a V2V channel measurement campaign using a channel sounder. Channel metrics such as channel gain, delay and Doppler spreads, eigenvalue decomposition and antenna correlations are derived from the ray tracing (RT) simulations as well as from the measurement data obtained from two different measurements in an urban fourway intersection scenario. The channel metrics are compared separately for line-of-sight (LOS) and non-LOS (NLOS) situation. Most power contributions arise from the LOS component (if present) as well as from multipaths with single bounce reflections. Measurement and simulation results show a very good agreement in the presence of LOS, as most of the received power is contributed from the LOS component. In NLOS, the difference is large because the ray tracer is unable to capture some of the multi bounced propagation paths that are present in the measurements. Despite the limitations of the ray-based propagation model identified in this work, the model is suitable to characterize the channel properties in a sufficient manner.

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“…A more realistic and scalable method based on ray tracing data interpolation and interfacing has been proposed in [27] to model urban propagation, which provides a way to compute average attenuation to reduce the computational load. The accuracy of a ray-tracing V2V channel model for urban intersections as compared with channel sounder measurement data has been studied in [28], where effects of road-side obstacles, such as traffic signs or parked vehicles, have also been discussed. Furthermore, the effects of the traffic signs along roads have been incorporated in channel modeling in [29], where they are decomposed into many small elements to embed the developed analytical models into raytracing tools, thus improving propagation modeling accuracy.…”

Section: B V2x Channel Modelingmentioning

confidence: 99%

Vehicular Communications: A Physical Layer Perspective

Liang

Peng

et al. 2017

IEEE Trans. Veh. Technol.

228

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Vehicular communications have attracted more and more attention recently from both industry and academia due to their strong potential to enhance road safety, improve traffic efficiency, and provide rich on-board information and entertainment services. In this paper, we discuss fundamental physical layer issues that enable efficient vehicular communications and present a comprehensive overview of the state-of-the-art research. We first introduce vehicular channel characteristics and modeling, which are the key underlying features differentiating vehicular communications from other types of wireless systems. We then present schemes to estimate the time-varying vehicular channels and various modulation techniques to deal with high-mobility channels. After reviewing resource allocation for vehicular communications, we discuss the potential to enable vehicular communications over the millimeter wave bands. Finally, we identify the challenges and opportunities associated with vehicular communications.

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Comparison of Ray Tracing and Channel-Sounder Measurements for Vehicular Communications

Cited by 38 publications

References 7 publications

Including general environmental effects in K-factor approximation for rice-distributed VANET channels

Including general environmental effects in K-factor approximation for rice-distributed VANET channels

Simulation and Measurement-Based Vehicle-to-Vehicle Channel Characterization: Accuracy and Constraint Analysis

Vehicular Communications: A Physical Layer Perspective

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