Picture of boy being examining by doctor at a tuberculosis sanatorium

Understanding our future through Open Access research about our past...

Strathprints makes available scholarly Open Access content by researchers in the Centre for the Social History of Health & Healthcare (CSHHH), based within the School of Humanities, and considered Scotland's leading centre for the history of health and medicine.

Research at CSHHH explores the modern world since 1800 in locations as diverse as the UK, Asia, Africa, North America, and Europe. Areas of specialism include contraception and sexuality; family health and medical services; occupational health and medicine; disability; the history of psychiatry; conflict and warfare; and, drugs, pharmaceuticals and intoxicants.

Explore the Open Access research of the Centre for the Social History of Health and Healthcare. Or explore all of Strathclyde's Open Access research...

Image: Heart of England NHS Foundation Trust. Wellcome Collection - CC-BY.

Spatial Fading Correlation model using mixtures of Von Mises Fisher distributions

Mammasis, K. and Stewart, R.W. and Thompson, J.S. (2009) Spatial Fading Correlation model using mixtures of Von Mises Fisher distributions. IEEE Transactions on Wireless Communications, 8 (4). pp. 2046-2055. ISSN 1536-1276

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

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.