A geometry-based stochastic MIMO model for vehicle-to-vehicle communications

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 non-stationarity 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

Répartition de diffuseurs pour l'ajustement des caractéristiques d'un canal de propagation simulé dans un contexte V2V

National audienceDans ce papier, nous proposons une méthode de type géométrique-stochastique pour modéliser des canaux de propagation d'un système de communication sans-fil de véhicule à véhicule et véhicule à infrastructure (V2X). Cette méthode permet de définir des scénarios dynamiques et sa flexibilité nous offre la possibilité de paramétrer les caractéristiques d'un canal de propagation. Nous montrons pour l'essentiel de quelle manière l'agencement et le nombre de diffuseurs de forme simple peuvent contribuer à influencer les statistiques de l'étalement des retards et la distribution des angles d'arrivée

Realistic wireless communication simulations for VANETS

International audienceVehicular Ad­hoc NETworks (VANETs) are mainly evaluated through simulations in which the choice of a realistic wireless channel model is a central point. Deterministic channel models bring good realism but need huge simulation time, whereas with statistical models the computational effort is reduced, but sadly so is the realism of the model. In this paper, we present a semi­deterministic channel model, called UM­CRT, based on a deterministic channel simulator, CRT (Communication Ray Tracer) and a statistical channel model, SCME-UM (Spatial Channel Model Extended - Urban Microcell). To integrate it into the NS­2 network simulator, we couple it to self­developed fully compliant 802.11p and 802.11n physical layers. Simulations in urban environment show both a good realism and a reduced computation time indicating that UM­CRT is adapted for VANETs simulations

Generalized Propagation Channel Model for 2GHz Low Elevation Links Using a Ray-tracing Method

Unmanned Aerial Vehicles (UAV) will increasingly be used for responding to emergencies or for law enforcement in civil surveillance applications. Transferring the enormous amounts of information from UAV-mounted cameras or sensors will require large bandwidths, unlike the information required for remotely controlling a UAV, thus necessitating higher frequency bands typically in the vicinity of 2 or 5 GHz. Novel hardware developments will need to rely on a versatile propagation channel model for the envisaged scenarios ranging from deep shadow urban areas to open fields. This paper studies more complex intermediate scenarios, which fall between the aforementioned ones, and which are more difficult to model. A semi-deterministic model, first developed for open, flat areas, has been generalized to accommodate any possible operational scenario and was tested in built-up areas. The model involves a stochastic part and a determinist which is a ray-tracing based part used to compute the long term mean (LTM) of the signal's coherent component

Requirements and test methods for vehicular antenna systems supporting cooperative ITS applications

Antenna systems are crucial for the link performance of§ any wireless systems, including those supporting cooperative intelligent transport system (C-ITS) applications. It is therefore of great importance to define performance metrics that are relevant for C-ITS applications and a framework for measuring the metrics. In this paper, we propose to measure performance by cumulative distribution functions based on the output SNR of the antenna system under test. The SNR samples are collected with respect to the time scales relevant for C-ITS applications. The framework is suitable for both computer simulations and over-the-air measurements and can handle antenna systems that are time-varying and have multiple output ports

Geometry-Based Stochastic Modeling and Estimation of Vehicle to Vehicle Channels

In this paper, a geometry-based stochastic channel model (GSCM) for vehicle-to-vehicle (V2V) wireless communica- tion is developed. The channel model reveals that the channel representation in delay-Doppler domain can be divided into four regions. In each region, the V2V channel can be modeled using a hybrid sparse/diffuse (HSD) model. Prior art on hybrid channel estimation for linear time-invariant channels is extended to the time-varying case. Furthermore, the effects of pulse shape leakage are explicitly determined and compensated. Simulation results shows that exploiting the V2V channel properties in the delay-Doppler domain, yields significantly improved channel estimates over unstructured approaches (more than 10 dB gain in SNR)

Multipath Parameter Estimation from OFDM Signals in Mobile Channels

We study multipath parameter estimation from orthogonal frequency division multiplex signals transmitted over doubly dispersive mobile radio channels. We are interested in cases where the transmission is long enough to suffer time selectivity, but short enough such that the time variation can be accurately modeled as depending only on per-tap linear phase variations due to Doppler effects. We therefore concentrate on the estimation of the complex gain, delay and Doppler offset of each tap of the multipath channel impulse response. We show that the frequency domain channel coefficients for an entire packet can be expressed as the superimposition of two-dimensional complex sinusoids. The maximum likelihood estimate requires solution of a multidimensional non-linear least squares problem, which is computationally infeasible in practice. We therefore propose a low complexity suboptimal solution based on iterative successive and parallel cancellation. First, initial delay/Doppler estimates are obtained via successive cancellation. These estimates are then refined using an iterative parallel cancellation procedure. We demonstrate via Monte Carlo simulations that the root mean squared error statistics of our estimator are very close to the Cramer-Rao lower bound of a single two-dimensional sinusoid in Gaussian noise.Comment: Submitted to IEEE Transactions on Wireless Communications (26 pages, 9 figures and 3 tables