Realistic IEEE 802.11p Transmission Simulations Based on Channel Sounder Measurement Data

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

doi:10.1109/vtcfall.2013.6692387

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…Scenario II: The communication and directions of vehicles are the same as in scenario I. This scenario includes building environments, in which the V2V communication packet delivery rates are based on channel measurements collected with the HHI channel sounder [23,24].…”

Section: B Driving Scenario Model Considering Communication Efficiencymentioning

confidence: 99%

Vehicle Following Control via V2V SIMO Communications Using MBD Approach

Sopajarn,

Booranawong,

Chumpol

et al. 2023

IEEE Access

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Autonomous vehicle systems have been significantly increasing in design complexity, including precise control, reliable communications, and data security. This paper presents a Model-Based Design (MBD) framework on MATLAB/Simulink to integrate the vehicle model, Vehicle-to-Vehicle (V2V) communication model, and autonomous driving scenario model. A vehicle-following control model is demonstrated to maneuver a follower vehicle using locations and velocities of the leader vehicle sent via V2V. The vehicle model consists of Time to Collision (TTC), velocity decision control, pathfollowing control, and vehicle dynamics. The follower vehicle decision is modeled by MathWorks Stateflowconsidering the important factors including velocities, positions, lanes, obstacles, and buildings that effect V2V communication efficiency. Simulink Design Verifier which is a formal verification tool was then used to verifier the TTC, velocity decision, and path following control. The test coverage analysis and test harness were repeated to generate test patterns with 100% coverage results. The experiments were done under the following communications and environmental conditions: single-input-single-output (SISO) without buildings, SISO with buildings, and single-input-multiple-output (SIMO) with buildings. The resulting communication packet delivery ratios were 100%, 95.32%, and 99.91%, respectively. This reveals that the proposed method can effectively model the vehicle following control and autonomous driving scenario including the effects of V2V communications efficiencies.

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Section: B Driving Scenario Model Considering Communication Efficiencymentioning

confidence: 99%

Vehicle Following Control via V2V SIMO Communications Using MBD Approach

Sopajarn,

Booranawong,

Chumpol

et al. 2023

IEEE Access

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“…Parameters for each new interval are chosen randomly, according to empirically estimated probabilities P (q 1 ) = 0.85 and P (q 2 ) = 0.15. ment, exhibit sudden performance loss at the distance of approx. 300 m. Underlying reasons were investigated based on channel sounder measurements in [1]. The authors have concluded, that the number of multipath channel components in this range is significantly larger as at any other position.…”

Section: Complexity Reduction: Realistic Casementioning

confidence: 99%

“…There exist different ways of modeling the propagation channel ranging from ray-tracing and replay models to stochastic channel models. For replay models, i.e., [1] the vehicular transmission is measured in realistic environment and the resulting trace is directly used as an input for simulator. However, the resulting models are constrained to reproduce the specific environment, namely the one where the measurements were taken.…”

Section: Introductionmentioning

confidence: 99%

Quantization-based complexity reduction for range-dependent modified Gilbert model

Shivaldova

Mecklenbräuker

2014

2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)

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In this contribution we propose an algorithm for dimension reduction of the previously introduced range-dependent modified Gilbert model. For reduction of the model dimension we suggest to jointly quantize model parameters estimated based on very narrow measurement intervals. We analyze the influence of the number of quantization levels on the model performance and based on this analysis find the optimal model dimension. Furthermore, we show that selected environmental and propagation effects, influencing the error pattern, can be identified by means of quantizing model parameters. Finally we demonstrate that these effects can be accurately reproduced by our model.

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