Polarimetric Wireless Indoor Channel Modelling Based on Propagation Graph

This paper generalizes a propagation graph model to polarized indoor wireless channels. In the original contribution, the channel is modeled as a propagation graph in which vertices represent transmitters, receivers, and scatterers, while edges represent the propagation conditions between vertices. Each edge is characterized by an edge transfer function accounting for the attenuation, delay spread, and the phase shift on the edge. In this contribution, we extend this modeling formalism to polarized channels by incorporating depolarization effects into the edge transfer functions and hence, the channel transfer matrix. We derive closed form expressions for the polarimetric power delay spectrum and cross-polarization ratio of the indoor channel. The expressions are derived considering average signal propagation in a graph and relate these statistics to model parameters, thereby providing a useful approach to investigate the averaged effect of these parameters on the channel statistics. Furthermore, we present a procedure for calibrating the model based on method of moments. Simulations were performed to validate the proposed model and the derived approximate expressions using both synthetic data and channel measurements at 15 GHz and 60 GHz. We observe that the model and approximate expressions provide good fit to the measurement data

Learning Parameters of Stochastic Radio Channel Models from Summaries

Estimating parameters of stochastic radio channel models based on new measurement data is an arduous task usually involving multiple steps such as multipath extraction and clustering. We propose two different machine learning methods, one based on approximate Bayesian computation (ABC) and the other on deep learning, for fitting stochastic channel models to data directly. The proposed methods make use of easy-to-compute summary statistics of measured data instead of relying on extracted multipath components. Moreover, the need for post-processing of the extracted multipath components is omitted. Taking the polarimetric propagation graph model as an example stochastic model, we present relevant summaries and evaluate the performance of the proposed methods on simulated and measured data. We find that the methods are able to learn the parameters of the model accurately in simulations. Applying the methods on 60 GHz indoor measurement data yields parameter estimates that generate averaged power delay profile from the model that fits the data

Joint Modeling of Received Power, Mean Delay, and Delay Spread for Wideband Radio Channels

We propose a multivariate log-normal distribution to jointly model received power, mean delay, and root mean square (rms) delay spread of wideband radio channels, referred to as the standardized temporal moments. The model is validated using experimental data collected from five different measurement campaigns (four indoor and one outdoor scenario). We observe that the received power, mean delay and rms delay spread are correlated random variables and, therefore, should be simulated jointly. Joint models are able to capture the structure of the underlying process, unlike the independent models considered in the literature. The proposed model of the multivariate log-normal distribution is found to be a good fit for a large number of wideband data-sets

60 GHz Wireless Propagation Channels: Characterization, Modeling and Evaluation

To be able to connect wirelessly to the internet is nowadays a part of everyday life and the number of wireless devices accessing wireless networks worldwide are increasing rapidly. However, with the increasing number of wireless devices and applications and the amount available bandwidth, spectrum shortage is an issue. A promising way to increase the amount of available spectrum is to utilize frequency bands in the mm-wave range of 30-300 GHz that previously have not been used for typical consumer applications. The 60 GHz band has been pointed out as a good candidate for short range, high data rate communications, as the amount of available bandwidth is at least 5 GHz worldwide, with most countries having 7 GHz of bandwidth available in this band. This large bandwidth is expected to allow for wireless communication with bit rates up to 7 Gbit/s, which can be compared to the typical WLAN systems of today that typically provide bit rates up to 0.6 Gbit/s. However, the performance of any wireless system is highly dependent on the properties and characteristics of the wireless propagation channel. This thesis focuses on indoor short range wireless propagation channels in the 60 GHz band and contains a collection of papers that characterizes, models and evaluates different aspects that are directly related to the propagation channel properties. Paper I investigates the directional properties of the indoor 60 GHz wireless radio channel based on a set of indoor measurements in a conference room. In the paper, the signal pathways and propagation mechanisms for the strongest paths are identified. The results show that first and second order interactions account for the major contribution of the received power. The results also show that finer structures, such as ceiling lamps, can be significant interacting objects. Paper II presents a cluster-based double-directional channel model for 60 GHz indoor multiple-input multiple-output (MIMO) systems. This paper is a direct continuation of the results in paper I. The model supports arbitrary antenna elements and array configurations and is validated against measurement data. The validation shows that the channel model is able to efficiently reproduce the statistical properties of the measured channels. The presented channel model is also compared with the 60 GHz channel models developed for the industry standards IEEE802.15.3c and IEEE802.11ad. Paper III characterizes the effect of shadowing due to humans and other objects. Measurements of the shadowing gain for human legs, metallic sheets, as well as metallic and plastic cylinders are presented. It is shown that the shadowing gain of these objects are fairly similar and that the shadowing due to the metal cylinder can be determined based on the geometrical theory of diffraction. Next, the shadowing due to a water-filled human body phantom is compared with the shadowing due to real humans. The results show that the water-filled phantom has shadowing properties similar to those of humans and is therefore suitable for use in 60 GHz human body shadowing measurements. Paper IV presents a novel way of estimating the cluster decay and fading. Previously, the cluster decay has usually been determined by performing a simple linear regression, without considering the effects of the noise floor and cluster fading. The paper presents an estimation method which takes these effects into account and jointly estimates both the cluster decay and cluster fading. It is shown that this estimation method can greatly improve the estimated parameters. Paper V evaluates the capacity improvement capability of spatial multiplexing and beamforming techniques for 60 GHz systems in an indoor environment. In this paper, beamforming refers to conventional gain focusing in the direction of the strongest propagation path. The paper uses a capacity metric that only depends on the multi-path richness of the propagation channel and the antenna aperture size. In the paper, it is shown that, when the link budget is limited due to electrically small antennas and long Tx-Rx separation distances, beamforming approximates the capacity of spatial multiplexing. However, spatial multiplexing is a worthwhile option when Rx SNR is favorable and a higher peak data rate is required. Paper VI describes different methods for the clustering of wireless multi-path components. In the literature, the clustering method that is predominantly used is the K-means algorithm, or a power-weighted version of K-means, called K-power means. In this paper, we point out that K-means is a special case of a Gaussian mixture model (GMM). The paper presents a clustering method based on a GMM. This method is able to handle arbitrary cluster spreads in the different dimensions better than the K-means algorithm. A power-weighted version of the GMM is also presented. In addition to this, a mixture model based on asymmetric Laplace distributions is also presented, with and without power-weighting. Paper VII is based on channel measurements in a small and a large room, where the Tx and Rx arrays have dual polarized elements. Using these measurements, the cross-polarization ratio (XPR) of the multi-path components are characterized. This gives valuable information on how the MPCs are affected by the propagation channel. A statistical description of the XPR is also needed for the development of a propagation channel model that supports polarization. The paper also investigates the eigenvalue spreads for single and dual polarized elements. Furthermore, the measurements include LOS and NLOS measurement, where the NLOS scenarios include water-filled human presented in paper III. The results show that the capacity can be greatly improved if dual-polarized elements are used, and that the XPR values are in general higher compared to lower frequencies

Spectral analyses of the dual polarization Doppler weather radar data.

Echoes in clear air from biological scatterers mixed within the resolution volumes over a large region are presented. These echoes were observed with the polarimetric prototype of the forthcoming WSR-88D weather radar. The study case occurred in the evening of September 7, 2004, at the beginning of the bird migrating season. Novel polarimetric spectral analyses are used for distinguishing signatures of birds and insects in multimodal spectra. These biological scatterers were present at the same time in the radar resolution volumes over a large area. Spectral techniques for (1) data censoring, (2) wind retrieval and (3) estimation of intrinsic values/functions of polarimetric variables for different types of scatterers are presented. The technique for data censoring in the frequency domain allows detection of weak signals. Censoring is performed on the level of spectral densities, allowing exposure of contributions to the spectrum from multiple types of scatterers. The spectral techniques for wind retrieval allow simultaneous estimation of wind from the data that are severely contaminated by migrating birds, and assessment of bird migration parameters. The intrinsic polarimetric signatures associated with the variety of scatterers can be evaluated using presented methodology. Algorithms for echo classification can be built on these. The possibilities of spectral processing using parametric estimation techniques are explored for resolving contributions to the Doppler spectrum from the three types of scatterers: passive wind tracers, actively flying insects and birds. A combination of parametric and non-parametric polarimetric spectral analyses is used to estimate the small bias introduced to the wind velocity by actively flying insects