Optimized Diffuse Scattering Selection for Large Area Real-Time Geometry-Based Stochastic Modeling of Vehicular Communication Links

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Optimized Diffuse Scattering Selection for Large Area Real-Time Geometry-Based Stochastic Modeling of Vehicular Communication Links

Rainer, Benjamin / Hofer, Markus / Bernado, Laura / Loschenbrand, David / Zelenbaba, Stefan / Anja, Dakic / Zemen, Thomas / Priller, Peter / Ye, Xiaochun / Li, Wenming

Abstract

In this paper we present a geometry-based stochastic channel model (GSCM) for mobile urban scenarios. GSCMs are very use case specific and high effort is needed to transfer existing ones to other scenarios. We propose to use OpenStreetMap data bootstrapping the geometry including the automatic placement of static, mobile and diffuse scatterers. We propose a method to distribute diffuse scatterers along buildings and roads. Our goal is to model complete city areas having the use case of real-time emulation of the wireless channel for vehicle-to-everything (V2X) communication in mind. In order to achieve this ambitious goal we propose a novel active scattering set selection based on locality-sensitive hashing (LSH). We show the trade-off between the number of selected diffuse scattering points by comparing the resulting power delay profile and Doppler spectral density to a measurement campaign.

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Document information

Title :

Optimized Diffuse Scattering Selection for Large Area Real-Time Geometry-Based Stochastic Modeling of Vehicular Communication Links

Contributors:

Rainer, Benjamin (author) / Hofer, Markus (author) / Bernado, Laura (author) / Loschenbrand, David (author) / Zelenbaba, Stefan (author) / Anja, Dakic (author) / Zemen, Thomas (author) / Priller, Peter (author) / Ye, Xiaochun (author) / Li, Wenming (author)

Published in:

2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM) ; 1-4

Publication date :

2020-11-23

Size :

1850257 byte

ISBN :

978-1-7281-6755-8

DOI :

https://doi.org/10.1109/ICMIM48759.2020.9298997

Type of media :

Conference paper