Spatial Fading Correlation model using mixtures of Von Mises Fisher distributions
Spatial Fading Correlation model using mixtures of Von Mises Fisher distributions
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DOI：
10.1109/twc.2009.080505
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发表时间：
2009-04
影响因子：
10.4
通讯作者：
K. Mammasis;R. Stewart;J. Thompson
中科院分区：
文献类型：
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作者：
K. Mammasis;R. Stewart;J. Thompson
本文推导了三维多径信道中天线阵列空间衰落相关函数的新表达式。特别是均匀圆形阵列（UCA）天线拓扑结构被认为是。新SFC函数的推导使用源自方向统计领域的概率密度函数（PDF），Von Mises Fisher（VMF）PDF。特别是新的SFC函数是基于混合建模的概念，因此使用VMF分布的混合。由于SFC函数取决于到达角（AoA）以及每个集群的功率，因此使用了更合适的功率方位角余纬度谱项。使用多输入多输出（MIMO）的实验数据，在室外驾驶测试活动在德国的分布的选择进行了验证。混合可以由任意数量的簇组成，这主要取决于在传播环境中遇到的杂波类型。在混合物中的各个集群的参数推导出这些参数的估计是使用软期望最大化（EM）算法实现的。结果表明，该模型与MIMO数据拟合良好。
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.