The Fisher-Bingham spatial correlation model for multielement antenna systems

In this paper, XXXX we study the effect of the elevation of incoming multipaths at a multielement antenna receiver by using a novel 3-D approach. It is shown that under a more general 3-D angle-of-arrival (AoA) model, namely, the Fisher-Bingham five-parameter (FB5) distribution, the spatial fading correlation (SFC) that is experienced between the adjacent antenna array elements decreases as the elevation increases. The FB5 distribution does not have a known series expansion, and therefore, the defining SFC integral can only numerically be evaluated. The proposed SFC function is further extended to capture the effect of multiple clusters of scatterers in the propagation channel. We, therefore, propose a mixture SFC function that is scaled according to the probability that each cluster contributes to the channel. The parameters of the individual components that constitute the mixture are estimated by using a soft expectation maximization (soft-EM) algorithm. The results indicate that the proposed model fits well with the data obtained from a multiple-input-multiple-output (MIMO) measurement campaign in the city of Ilmenau, Germany

3-dimensional channel modeling using spherical statistics for multiple input multiple output systems

This model is a 2D model where the propagating plane waves are assumed to arrive only from the azimuthal direction and does not include the elevation domain. As a result of this assumption the derived angle of arrival (AoA) distribution is characterized only by the azimuth direction of these waves. In this paper the distribution of scatterers is modeled in a novel 3D approach. The Von Mises Fisher (VMF) probability density function (PDF) is used to describe their distribution within the propagation environment in azimuth and coelevation. As a result the AoA distribution of the incoming multipaths is characterized in the same way. More specifically the model proposed uses a mixture of VMF distributions. A mixture can be composed of any number of clusters and this is environment/clutter specific. The parameters of the individual clusters of scatterers within the mixture are derived and an estimation of those parameters is achieved using the soft-expectation maximization (EM) algorithm. The results indicate that the proposed model fits well with MIMO experimental data obtained from a measurement campaign in Germany. The measurements obtained from the RUSK channel sounder were post-processed using the RiMAX algorithm. The data was subsequently clusterized using the soft-EM for mixtures of VMF distributions

Spatial Fading Correlation model using mixtures of Von Mises Fisher distributions

In this paper new expressions for the Spatial Fading Correlation (SFC) functions of Antenna Arrays (AA) in a 3-dimensional (3D) multipath channel are derived. In particular the Uniform Circular Array (UCA) antenna topology is considered. The derivation of the novel SFC function uses a Probability Density Function (PDF) originating from the field of directional statistics, the Von Mises Fisher (VMF) PDF. In particular the novel SFC function is based on the concept of mixture modeling and hence uses a mixture of VMF distributions. Since the SFC function is dependent on the Angle of Arrival (AoA) as well as the power of each cluster, the more appropriate power azimuth colatitude spectrum term has been used. The choice of distribution is validated with the use of Multiple Input Multiple Output (MIMO) experimental data that was obtained in an outdoor drive test campaign in Germany. A mixture can be composed of any number of clusters and this is mainly dependent on the clutter type encountered in the propagation environment. The parameters of the individual clusters within the mixture are derived and an estimation of those parameters is achieved using the soft-Expectation Maximization (EM) algorithm. The results indicate that the proposed model fits well with the MIMO data

Modeling scatterer clusters in 3D using spherical statistics for 4G communications

Paper describes the modelling of scatterer clusters in 3D using spherical statistics for 4G communications

Three-dimensional channel modelling using spherical statistics for multiple-input multiple-output systems

Recently, the third generation partnership standards bodies (3GPP/3GPP2) have defined a two-dimensional channel model for multiple-input multiple-output (MIMO) systems, where the propagating plane waves are assumed to arrive only from the azimuthal direction and therefore not include the elevation domain. As a result of this assumption, the derived angle-of-arrival (AoA) distribution is characterised only by the azimuth direction of these waves. The AoA distribution of multipaths is implemented with a novel three-dimensional approach. The von Mises- Fisher (VMF) probability density function is used to describe their distribution within the propagation environment in both azimuth and co-latitude. More specifically, the proposed model uses a mixture of VMF distributions. A mixture can be composed of any number of clusters and this is clutter specific. The parameters of the individual cluster of scatterers within the mixture are derived and an estimation of those parameters is achieved using the spherical K-means algorithm and also the expectation maximisation algorithm. Statistical tests are provided to measure the goodness of fit of the proposed model. The results indicate that the proposed model fits well with MIMO experimental data obtained from a measurement campaign in Germany

Three-dimensional channel modelling using spherical statistics for smart antennas

The distribution of angle of arrival of multipaths in a novel three- dimensional approach is modelled. The approach followed takes into consideration a cluster of scatterers local to the mobile and models it using mixtures of Von Mises Fisher (VMF) distributions. Real MIMO experimental data was collected in a drive test campaign in Ilmenau city of Germany and was used to validate the proposed model. Results show a good match between the proposed model and the two-dimensional experimental histogram