Geometry-based stochastic MIMO channel models using the concept of multipath clusters are advantageous to model the spatial structure of the channel accurately and in a intuitive manner. However, they are difficult to parameterize. This becomes evident in current (quasi-)standard models, which provide default parameters to cover the environments of interest, yet the model fit is not always convincing. The parameterization is not accurate enough. We present an automatic framework to obtain the models' cluster parameters, which have significant impact on the model accuracy. After applying the framework to indoor MIMO channel measurements, we discuss the results for following model parameters: the cluster delay spread, the cluster angular spreads, the number of paths within a cluster, and the number of clusters at each time instant. We observe significant correlations between cluster parameters, which can be used to considerably improve current channel models.
展开▼
