Overview of vehicle-to-vehicle radio channel measurements for collision avoidance applications

In this paper we present an overview of a vehicle-to-vehicle radio channel measurement campaign at 5.6GHz. The selected measurement scenarios are based on important safety-related applications. We explain why these scenarios are interesting from the aspect of radio propagation. Further we describe the power-delay profile and the Doppler spectral density of two situations especially suitable for collision avoidance applications: A traffic congestion situation where one car is overtaking another one, and a general line-of-sight obstruction between the transmitter and the receiver car. The evaluations show that in these situations the radio channel is highly influenced by the rich scattering environment. Most important scatterers are traffic signs, trucks, and bridges, whereas other cars do not significantly contribute to the multipath propagation

Physical-statistical modeling of dynamic indoor power delay profiles

This paper presents a physical-statistical radio channel power delay profiles model for room-to-room communication systems combining the room electromagnetic theory for modeling deterministic channel components with a geometry-based stochastic channel model with time-variant statistics for modeling stochastic components. The deterministic channel component, i.e., mean power delay spectrum, is comprised of specularly reflected paths plus diffuse components due to scattering and diffraction. The specular components are modeled with a set Dirac function, whereas the diffuse components modeling approach is a room electromagnetic theory-based model. Dynamic indoor communication channels are characterized by a non-stationary time-and delay-fading process due to changes in the environment. We analyze and model the time-delay variability of channels using K-factor for small-scale variations and the t-location scale distribution parameters for large-scale variations. It turns out that these parameters cannot be assumed to be constant in time and delay. After modeling of time-delay variations of the first order statistics, we generate channel realizations with appropriate second order statistics. As the result, the presented model enables to describe the evolution of the power delay profile in the time domain

Characterization of vehicle-to-vehicle channels in various scenarios

Projecte final de carrera fet en col.laboració amb FTW i Technische Universität WienEnglish: In this thesis we will characterize the vehicle-to-vehicle channel in various scenarios based in risk situations. We estimate diferent channel parameters as the time-varying root mean square (rms) delay and Doppler spreads, as well as the stationarity time. Also, we present a new approach for the identiï¬ cation of scattering objects. We move one step forward from the method used until now, where the identiï¬ cation was done visually based on the power delay proï¬ le and video material recorded in the measurement campaigns. We propose to use the local scattering function (LSF), which brings the Doppler domain into play. The LSF is a multitaper estimate of the 2 dimensional power spectral density in delay and Doppler. Each peak of the LSF is composed by several multipath components (MPCs) coming from the same scattering object. Our approach consists of two steps: detection of the relevant peaks, and assignment of MPCs to the scattering objects. We do that by using a clustering algorithm. We apply the method to a set of vehicular radio channel measurements and extract the time-varying cluster parameters. The clusters have ellipsoidal shape with their longer axes in the Doppler domain. The ï¬ rst detected cluster presents different properties than the rest of the clusters, being larger, constant in time, and more static in the delay-Doppler plane. By identifying properly only the relevant scattering objects, vehicular channel models can be written in simpler ways than current approaches, such as the geometry- based stochastic channel model, very well suited for modeling the vehicular channel

Parametrization of the local scattering function estimator for vehicular-to-vehicular channels

Non wide-sense stationary (WSS) uncorrelated scatterering (US) fading processes are observed in vehicular communications. To estimate such a process under additive white Gaussian noise we use the local scattering function (LSF). In this paper we present an optimal parametrization of the multitaper-based LSF estimator. We do this by quantizing the mean square error (MSE). For that purpose we use the structure of a twodimensional Wiener filter and optimize the parameters of the estimator to obtain the minimum MSE (MMSE). We split the observed fading process in WSS regions and analyze the influence of the estimator parameters and the length of the stationarity regions on the MMSE. The analysis is performed considering three different scenarios representing different scattering properties. We show that there is an optimal combination of estimator parameters and length of stationarity region which provides a minimum MMSE