Non-WSSUS vehicular channel characterization in highway and urban scenarios at 5.2GHz using the local scattering function

Abstract

Non-WSSUS vehicular channel characterization in highway and urban scenarios at 5.2 GHz using the local scattering function. 9-15. Paper presented at International Workshop on Smart Antennas (WSA), .

Directional Analysis of Vehicle-to-Vehicle Propagation Channels

“…In order to reduce the computational complexity, we use measurement data with a bandwidth of 20 MHz, out of the full 240 MHz, centered around 5.6 GHz, and a temporal window of length 19.4 ms (64 snapshots). This temporal window corresponds to a Doppler resolution of 52 Hz and is selected based on the estimated stationarity time of the channel (see [14] for details), which is 97.6 ms, 374.4 ms, and 1337.9 ms for the intersection, congestion and obstructed-LOS scenarios, respectively. Due to the computational efforts of estimating parameters using SAGE, we limit the analysis to a temporally sparse subset of the measurements data; every 0.5 s in the intersection, every 1 s in the other two.…”

Measurement-Based Modeling of Vehicle-to-Vehicle MIMO Channels

“…1 for a typical sample plot): (i) the LOS path is always strong, (ii) significant energy is available through discrete components, typically represented by a single tap (e.g., the diagonal "lines" in Fig. 1), (iii) discrete components typically move through many delay bins during a measurement; this implies that the common assumption of WSSUS is violated [18], (iv) discrete components may stem from mobile as well as static scattering objects, and (v) the LOS is usually followed by a tail of weak components. Analysis of the amplitude statistics of the taps immediately following the LOS tap shows that they can be well described by a Rayleigh distribution [20].…”

“…This modeling approach has a number of important benefits: (i) it can easily handle non-WSSUS channels, (ii) it provides not only delay and Doppler spectra, but inherently models the MIMO properties of the channel, (iii) it is possible to easily change the antenna influence, by simply including a different antenna pattern, (iv) the environment can be easily changed, and (v) it is much faster than deterministic ray tracing, since only single (or double) scattering needs to be simulated. A few geometrical VTV models with scatterers placed on regular shapes have been proposed, e.g., [17], however, their underlying assumption of all scatterers being static does not agree with results reported in measurements [18]. In this paper, we present a GSCM for MIMO VTV channels based on a more realistic placement of static and dynamic scatterers and parameterize it using results from an extensive measurement campaign on rural roads near Lund, Sweden.…”

A Non-Stationary MIMO Vehicle-to-Vehicle Channel Model Derived From the Geometrical T-Junction Model

“…The majority of channel models that can be found in the literature rely on the stationarity assumption. However, measurement results for V2V channels in (Paier et al, 2008) have shown that the stationarity assumption is valid only for very short time intervals. This fact arises the need for non-stationary channel models.…”

“…This assumption makes our channel model non-stationary. The correlation properties of a non-stationary channel model can be obtained using a multi-window spectrogram (Paier et al, 2008). For rapidly changing spectral content however, finding an appropriate time window size is a rather complicated task.…”