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Abstract-Vehicle-to-vehicle (VTV) wireless communications have many envisioned applications in traffic safety and congestion avoidance, but the development of suitable communications systems and standards requires accurate models for the VTV propagation channel. In this paper, we present a new wideband multiple-input-multiple-output (MIMO) model for VTV channels based on extensive MIMO channel measurements performed at 5.2 GHz in highway and rural environments in Lund, Sweden. The measured channel characteristics, in particular the nonstationarity of the channel statistics, motivate the use of a geometry-based stochastic channel model (GSCM) instead of the classical tapped-delay line model. We introduce generalizations of the generic GSCM approach and techniques for parameterizing it from measurements and find it suitable to distinguish between diffuse and discrete scattering contributions. The time-variant contribution from discrete scatterers is tracked over time and delay using a high resolution algorithm, and our observations motivate their power being modeled as a combination of a (deterministic) distance decay and a slowly varying stochastic process. The paper gives a full parameterization of the channel model and supplies an implementation recipe for simulations. The model is verified by comparison of MIMO antenna correlations derived from the channel model to those obtained directly from the measurements.

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Vehicular communication channels are characterized by a non-stationary time-and frequencyselective fading process due to fast changes in the environment. We characterize the distribution of the envelope of the first delay bin in vehicle-to-vehicle channels by means of its Rician K-factor. We analyze the time-frequency variability of this channel parameter using vehicular channel measurements at 5.6 GHz with a bandwidth of 240 MHz for safety-relevant scenarios in intelligent transportation systems (ITS). This data enables a frequency-variability analysis from an IEEE 802.11p system point of view, which uses 10 MHz channels. We show that the small-scale fading of the envelope of the first delay bin is Rician distributed with a varying K-factor. The later delay bins are Rayleigh distributed.Manuscript received yyyyyyy.2014. L. Bernadó and T. Zemen (corresponding author) are with Forschungszentrum Telekommunikation Wien (FTW), 2 We demonstrate that the K-factor cannot be assumed to be constant in time and frequency. The causes of these variations are the frequency-varying antenna radiation patterns as well as the time-varying number of active scatterers, and the effects of vegetation. We also present a simple but accurate bimodal Gaussian mixture model, that allows to capture the K-factor variability in time for safety-relevant ITS scenarios. I. INTRODUCTIONIntelligent transportation systems (ITS) have gained much interest in the last years. They have the potential to strongly reduce the rate of accidents and environmental pollution with the help of reliable wireless vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. New receiver algorithms for vehicular communications are first evaluated using numeric link level simulations which rely on accurate channel models. Key factors influencing the wave propagation in vehicular channels are the low position of the antenna on the rooftop of the vehicle, the larger number of metallic objects close to the communication link, and the high mobility of the transmitter (TX) and the receiver (RX). The combination of all these aspects, as in vehicular communications, give rise to a non-stationary fading process. Therefore, it is necessary to study and characterize the small-scale fading statistics in vehicular channels, see e.g. [1]-[9], since non-stationary vehicular channel properties have a large impact on the performance of a communication system [10], [11].In this paper we particularly focus on the characteristic of the Rician K-factor of non-stationary vehicular channels. The K-factor K = 10log 10 (r 2 /2σ 2 ) [dB] (1)is defined as the ratio of the energy of the specular part r 2 and the diffuse part 2σ 2 of the received signal [12], [13]. Often, the specular part consists only of the line of sight (LOS) component, but specular components can also stem from flat good reflecting surfaces (e.g. traffic signs) where the impinging wave is reflected into a single direction.

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), .