Claude Oestges

Survey of channel and radio propagation models for wireless MIMO systems

This paper provides an overview of the state-of-the-art radio propagation and channel models for wireless multiple-input multiple-output (MIMO) systems. We distinguish between physical models and analytical models and discuss popular examples from both model types. Physical models focus on the double-directional propagation mechanisms between the location of transmitter and receiver without taking the antenna configuration into account. Analytical models capture physical wave propagation and antenna configuration simultaneously by describing the impulse response (equivalently, the transfer function) between the antenna arrays at both link ends. We also review some MIMO models that are included in current standardization activities for the purpose of reproducible and comparable MIMO system evaluations. Finally, we describe a couple of key features of channels and radio propagation which are not sufficiently included in current MIMO models.

Dual-polarized wireless communications: from propagation models to system performance evaluation

In this paper, we address the potential benefits of dual-polarized arrays in multi-antenna wireless systems. After an extensive literature overview of experimental data, we present a new and simple analytical framework to model dual-polarized Rayleigh and Ricean fading channels for arbitrary array sizes. The model relies on a limited number of physical parameters, such as the channel spatial correlations, the channel co-polar and the cross-polar ratios and the antenna cross-polar discrimination. Then, we investigate the multiplexing advantage of dual-polarized transmissions through the evaluation of the ergodic mutual information, for both TITO and MIMO systems. Finally, the performance of two space-time coding schemes (Alamouti OSTBC and uncoded spatial multiplexing) is evaluated via a detailed analysis of the pairwise error probability.

Propagation modeling of MIMO multipolarized fixed wireless channels

This paper addresses the extension of a stochastic geometry-based scattering model to multipolarized transmissions. The initial approach is based on a geometrical distribution of obstacles derived from known power-delay profiles. Each scattering process is statistically described by a matrix reflection coefficient corresponding to dual-polarization states. Ultimately, the model allows us to simulate the effects of the range on K-factor, delay-spread, Doppler spectrum, channel correlations and capacity, branch power ratio, and cross-polar discrimination. Simulation results are compared with existing measurements at 2.5 GHz. The proposed model is then used to investigate various dual-polarization 2 /spl times/ 2 multiple-input-multiple-output (MIMO) schemes such as 0/spl deg//90/spl deg/ or /spl plusmn/45/spl deg/, as well as to optimize the design of multipolarized MIMO schemes.

The COST 2100 MIMO channel model

The COST 2100 channel model is a geometry- based stochastic channel model (GSCM) that can reproduce the stochastic properties of MIMO channels over time, frequency, and space. In contrast to other popular GSCMs, the COST 2100 approach is generic and flexible, making it suitable to model multi-user or distributed MIMO scenarios. In this article a concise overview of the COST 2100 channel model is presented. Main concepts are described, together with useful implementation guidelines. Recent developments, including dense multipath components, polarization, and multi-link aspects, are also discussed.

Characterization of space-time focusing in time-reversed random fields

This paper proposes various metrics to characterize space-time focusing resulting from application of time reversal techniques in richly scattering media. The concept and goals of time reversal are presented. Pertinent metrics describing both the time and space focusing effects are outlined. Two examples based on a model of discrete and continuous scattering media are used to illustrate how the proposed metrics vary as a function of various system and channel parameters, such as the bandwidth, delay and angle spreads, number of antennas, etc.

Experimental Characterization and Modeling of Outdoor-to-Indoor and Indoor-to-Indoor Distributed Channels

We propose and parameterize an empirical model of the outdoor-to-indoor and indoor-to-indoor distributed (cooperative) radio channel, using experimental data in the 2.4-GHz band. In addition to the well-known physical effects of path loss, shadowing, and fading, we include several new aspects in our model that are specific to multiuser distributed channels: 1) correlated shadowing between different point-to-point links, which has a strong impact on cooperative system performance; 2) different types of indoor node mobility with respect to the transmitter and/or receiver nodes, implying a distinction between static and dynamic shadowing motivated by the measurement data; and 3) a small-scale fading distribution that captures more severe fading than that given by the Rayleigh distribution.

Non-Stationary Narrowband MIMO Inter-Vehicle Channel Characterization in the 5-GHz Band

In this paper, we describe measurements and models of 30 × 30 narrowband multiple-input-multiple-output (MIMO) vehicle-to-vehicle (V2V) radio propagation channels at 5.3 GHz. Four environments were considered: a campus, a highway, a suburban area, and an urban area. Since the scattering environment may rapidly change in V2V communications, we first investigate the validity of the wide-sense stationarity (WSS) assumption for such channels using the correlation matrix distance (CMD), which is a metric for the characterization of the MIMO channel nonstationarity. Moreover, statistical channel models were developed for these environments, which take into account the non-stationary behavior of the measured V2V channels. The large-scale fading was found to be lognormally distributed, whereas the small-scale fading was characterized by the flexible Weibull distribution. Finally, the non-stationary behavior of both large-scale fading and small-scale fading statistics was investigated.

Editorial: advances in propagation modeling for wireless systems

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A physical scattering model for MIMO macrocellular broadband wireless channels

This paper presents a physical scattering model that predicts multiple-input multiple-output (MIMO) channel characteristics conforming well to experimental observations in macrocells. Our approach is to start with a given single-input single-output power-delay profile (defined for specific range, bandwidth and antenna parameters) and fit a scattering model that characterizes the MIMO channel. From the derived scattering model and antenna array configurations, the MIMO channel is computed using a ray-based method. Simulations of several MIMO channels are shown to exhibit experimentally observed channel correlations, antenna beamwidth effect, range dependency, and frequency selectivity.

A Body Area Propagation Model Derived From Fundamental Principles: Analytical Analysis and Comparison With Measurements

Using wireless sensors worn on the body to monitor health information is a promising new application. To realize transceivers targeted for these applications, it is essential to understand the body area propagation channel. Several numerical, simulated, and measured body area propagation studies have recently been conducted. While many of these studies are useful for evaluating communication systems, they are not compared against or justified by more fundamental physical models derived from basic principles. This type of comparison is necessary to provide better physical insights into expected propagation trends and to justify modeling choices. To address this problem, we have developed a simple and generic body area propagation model derived directly from Maxwells equations revealing basic propagation trends away, inside, around, and along the body. We have verified the resulting analytical model by comparing it with measurements in an anechoic chamber. This paper develops an analytical model of the body, describes the expected body area pathloss trends predicted by Maxwells equations, and compares it with measurements of the electric field close to the body.